Making Disability Data Work for You

A Community Data Toolkit: Part 1

January 2014	

Acknowledgments

This has been produced by DWP’s Disability Analysis Division. 

Note: although this toolkit has been written as part of Fulfilling Potential, it is relevant to anyone who wants to use local data. It is not just for people/groups who are interested in disability issues.

 Making Disability Data Work for You

How to use local information to improve people’s lives

Do you want to improve disabled people’s lives?

Do you want to use information which can help you make better decisions?

Are you unsure of what information is out there, how to get hold of it, or how to use it?

Would you like to know more about different sorts of information and how it can be used?

Improving the lives of disabled people, like any other goal, relies on using information to help make the right choices and do things that work. To make a difference, we first need to know lots of things, like:
-	What do disabled people want or need?
-	What issues do disabled people face in their daily lives?
-	What prevents disabled people from participating fully, from getting a job, to taking part in community or leisure activities?  

This Community Data Toolkit aims to provide you with help and guidance to find and use information, or ‘data’, with confidence, and in turn, use it to help make better decisions. 

We would welcome any feedback you can give us on using the toolkit. Please send any thoughts, comments or queries you have about the toolkit to fulfilling.potential@dwp.gsi.gov.uk 

 Making Disability Data Work for You

Contents

Introduction
Chapter 1 - Principles of data
What is data?
Why use data?
Types of data
Risks and assessing data

Chapter 2 – What data is available
Disability
Education
Employment
Income
Health and Wellbeing
Transport
Housing
Other disability data

Chapter 3 –Using data
How to analyse data
Common types of analysis
How to interpret data

Chapter 4 – Evaluation of the Community Data Toolkit
Annex A – Links to data
Annex B – Definition of disability
Annex C - Types of data
Annex D - Types of analysis
References
Glossary
Index

Introduction

1.	The Government’s vision is of a society that enables all disabled people to fulfil their potential and have an equal opportunity to realise their aspirations and play a full role in society.  This vision is being taken forward in the Government’s disability strategy “Fulfilling Potential – Making it Happen”.  This document and its supporting Action Plan also show how we will be meeting our responsibilities under the UN Convention on the Rights of Disabled People.

2.	Disability can impact an individual’s day to day life in many different ways.  In section 4 of “Fulfilling Potential – Making it Happen” we have identified six broad outcomes and a range of supporting indicators which we will be using to measure trends in the areas where disabled people face the most barriers. These are national indicators, and do not take into account the geographical variations in barriers, attitudes and day-to-day living.

3.	We have, therefore, worked with disability organisations to create this toolkit to compliment national level data. The toolkit will enable organisations to find the information they need to make changes, improve outcomes and generally help the lives of disabled people.

4.	Although this toolkit will not be able to provide national data at a local level, it will provide a useful number of sources to enable organisations to develop an understanding of their community.  

5.	The toolkit will help organisations understand the most important local issues. It will provide them with the information they need to plan action, influence local decision making and have a stronger role in their communities. 

6.	The impact of a disability and the barriers that disabled people face can differ depending on location or community. For example, the barriers someone faces in a large city are not the same as those the same person would face in a rural community. 

7.	All organisations including local community groups need to know their target audience.  For example, in order to provide a local service, a local community organisation needs to know who their customers will be and if there are any specific large ethnic, religious or gender groups whose needs they will need to consider when developing their services. 

8.	The focus of Part 1 of the Toolkit is to show you what data has been published and how to use that data. However, as we are using existing data there are limitations, and as such it is usually not possible to identify data for very small areas, for example postcode area. When we mention local area in this toolkit, we mean local authority area. To get more localised data you will have to collect your own data. This will be the focus for Part 2 of the toolkit, due to be published in Spring 2014. 

9.	Another point to note is that although this toolkit will cover what data is available for our 8 main themes (Disability, Education, Employment, Income, Health and Wellbeing, Transport, Housing, and other disability data), not all of the themes will have the same breadth of data. For example there is limited local data available on income, but with Department of Health’s and Public Heath England’s Outcomes Frameworks there is very good data under the Health and Wellbeing theme. 

10.	When doing the research for this toolkit the smallest geographical area we could find disability related data for, was electoral ward level. We will welcome your feedback, if you have been able to find published data for a smaller area. Please contact us at fulfilling.potential@dwp.gsi.gov.uk 

Chapter 1 – Principles of data

What is data?

11.	Data is the collection of facts or information. Data can be numbers, words, measurements, observations or even just descriptions of things. When put together the data can be analysed to provide an insight on many matters.

12.	In theory data is limitless and present everywhere in the universe. Everything we do and say is data, but it is the organised collection of the data that makes it useable and powerful. 
 
Why use data?
13.	You can use data to help:
o	Understand a problem or issue;
o	Support a decision;
o	Discover useful information ;
o	To improve the understanding of a community.

14.	It is about gathering information, filtering what has been collected and using it to see what is happening. For example:

Example 1:
In 1854 an outbreak of cholera occurred in Soho (London).  At the time the accepted theory was that diseases were caused by ‘bad air’.  However, Doctor Snow was not sure.  He found out where the victims lived and created a map showing that nearly all the victims had lived in the same small area (a cluster).  The Doctor visited the area and found that the cluster centred on a public water pump.  His further investigation also found that even the few victims who did not live within the ‘cluster area’ regularly use the same water pump.  By removing the handle of the pump to stop it being used, the cholera epidemic was stopped.

This and further research by Doctor Snow, linking cholera to dirty water is now considered one of the major events in the history of public health.

15.	There are two main questions that data is used to answer:
•	What is happening?
•	Why is it happening?
To answer these questions some sort of analysis needs to be carried out.

16.	The easiest and cheapest way to do this is by using existing data. Lots more data has become available in recent years. However, it is important to note that the data you see is the last part of the research process. A lot of work has gone into collecting data, and it is important to be able to tell if the data meets your needs. 

17.	It is easy to get confused about what the data is saying, as there are many different types of data and ways you can collect and analyse it.

18.	There is a set process when wanting to use some data: 

•	Step 1: think about what you want the data for – what do you need to know? What is the overarching theme? This can be as big or small as you like, for example, attitudes towards disabled people or number of accessible buses. 
•	Step 2: come up with ideas. The aim is to try and find all possible measures of your chosen theme in Step 1. The reason behind this is to get your theme broken down into small manageable questions. For example if you try to look up ‘attitudes’ as a whole you will not be able to find anything. However, if you split attitudes into ‘media’, ‘public’ and ‘work’ attitudes, these are more manageable questions. 
•	Step 3:  repeat Step 2 until you cannot break the measures down any further. This may need to be repeated one or more times. However, it is important to keep your theme (what you want the data for) in mind when carrying out step 3 as it is easy to get carried away.  

19.	Scenario 1 below provides a fictional example of how to find what data you need. 

Scenario 1: Lucy is opening a community support group in Liverpool, and wants to know “what groups could I run?”

Her first step was to think about what this question really means, and what she really wants to know – who are my potential customers? This was broken down into manageable chunks, ‘Disabled People’, ‘Carers’ and ‘Other competitors?’ as can be seen in the chart below. 

After repeating the process to break down the topics as much as she could, she ended up with eight questions (the ones in oval boxes below):
•	How many competitors are there in Liverpool?
•	What do these competitors offer?
•	How many carers are there in Liverpool?
•	How many disabled people are there in Liverpool?
•	What is their impairment?
•	What is their religion?
•	What is their gender?
•	Do they have any special requirement needs?

This meant that Lucy was able to focus her search to these eight questions and get the data she needed to answer her main question – what support groups could she run in Liverpool.

Types of data

20.	Once you have decided what you want the data for, the next stage is to decide what data you need.  There are many different types of data. 

21.	Unfortunately there is a lot of terminology and jargon when looking at different types of data. However, the meaning behind them is quite simple. There are two main sources of data:
o	Research Data 
This is often called survey data. It is data that has been collected from a number of people in an organised way (for example, by using a survey) because an organisation or individual wants to know something. More information on research data can be found in Annex C.
o	Administrative data 
This is information which organisations collect as part of running their business. For example, service providers collect information on who their service users are, their ages, gender etc. in order to provide their services. This information, if managed well, can be used to conduct analysis. More information on administrative data can be found in Annex C.

22.	Within these sources of data there are many different types of data:
o	Qualitative data
This is information that has been collected through in-depth conversations with people. It is ‘a conversation with a purpose’.  More information on qualitative data can be found in Annex C.
o	Quantitative data 
This is data that can be measured and analysed using numbers. More information on quantitative data can be found in Annex C.
o	Cross sectional data
This is data gathered from a survey of people at a specific point in time, so provides a picture of society for that period. What makes it unique is that every time the survey is asked, it is asked to a different group of people. More information on cross-sectional data can be found in Annex C.
o	Longitudinal data
This data looks at the changes in a group of individuals lives over a period of time. More information on longitudinal data can be found in Annex C.

o	Evaluations
There are many different types of evaluations. However, what they all do is measure the effects a policy/change has on society. More information on evaluations can be found in Annex C.

Risks and assessing data

23.	Not all public data is good quality – there are many pitfalls in using bad or inappropriate data. Just because the data has been published does not imply that it is good to use, or that the results it produces are accurate. 

24.	The data quality checklist below shows the most common things to look out for.

	
	Is it the right type of data? 
	
	How was the data collected? 
	
	Does the question / questionnaire make sense?	
	Does the question match your requirements
	
	Has the data been cleaned? 
	
	How many people answered the question? 	
	Does the data show what you expected?
	
	Is the data biased?

25.	Is it the right type of data? As previously discussed there are many types of data, and it is essential that you use the right type. For example if you want data that represents your target group, then you should not use qualitative data.

26.	How was the data collected? There are many different ways to collect data, from telephone interviews, postal surveys, face-to-face interviews and online surveys. Each of these have their advantages and disadvantages. When the research is about disabled people it is vital that you look at how the data was collected, as not all types of surveys are accessible to all. For example, if you are researching elderly disabled people it is best not to use an online survey. However, an online survey may actually be better than a face-to-face interview for some people; for example, people with hearing impairments or those who find a face-to-face interview intrusive.

27.	Does the question make sense? Developing a good questionnaire is hard, it needs to: be easy to understand; not contain any jargon; and not to be leading, for example, “pollution is bad, what do you think of pollution?” If a question does not meet these rules then the people answering the question are likely to either skip it or guess at an answer, making their responses unusable.

28.	Does the question match your requirements? If a question is not a direct match to the issue you are investigating, then it is better not to use it as you cannot guess or assume what public responses will be. Also you cannot assume than an answer to one question can be used to answer another question. 

29.	Has the data been cleaned? There can be many errors when inputting data. Analysts are human and make mistakes. Most organisations clean their data before it is released, however, it is always safer to check first. Before doing any analysis, look at your data does it make sense, for example if someone is aged 234 then that is likely to be a typing mistake and that individuals age needs to be removed from the data.

30.	How many people answered the question? The technical term for this is ‘sample size’, generally speaking the higher the sample size the better, although it is essential that you ask the right people. As a basic rule if you are looking at quantitative data a sample size of 1,000 is good, for qualitative data a sample size of 10-25 is good.

31.	Is the data biased? There are many different types of bias.  The main issue is when the people who answered the question do not represent your target group, meaning that results are not accurate.

32.	Please remember if the quality of data is poor, then your analysis will be poor. You cannot manipulate data to improve its quality after it has been collected. 

Chapter 2 – What data is available

33.	To show how much local level data is available, we have split the data into eight ‘themes’. The following sections will look into what types of data are available under each theme heading and how it can be accessed and used.

34.	We will also state whether the data is at a national, regional or local level. Throughout this toolkit, we will define these as:
•	National: data which looks at the whole of the nation, which could be the UK, Great Britain or just England.
•	Regional: this is a set way of dividing England into 9 regions; North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East of England, London, South East and South West. Also, if the survey covers any of the other countries in the UK then they will be added as a region. For example, if the data covers Great Britain we will have 11 regions, all of the English regions above as well as Scotland and Wales.
•	Local: if the data goes down to a local level, this means that you can get data for each Local Authority, unless specified differently.

35.	As mentioned previously, it is not possible to get disability data for the smallest geographical area. For example, you cannot get disability related data for your postcode area. The smallest area that it is possible to get disability related data is electoral ward level. An electoral ward is a section of a local authority area.  

36.	The following table shows the smallest geographical breakdown available for each theme. 

Theme	Smallest geographical area 	
Disability	Electoral Ward	
Education	Local Authority	
Employment	Local Authority	
Income	Constituency	
Health and Wellbeing	Local Authority	
Transport	Region	
Housing	Local Authority	
Other disability data	Electoral Ward 	

37.	The main reason behind not being able to get data for small geographical areas is sample size. Confidentiality is an important aspect in research, it is essential that participants remain anonymous. As such, if the group you are trying to investigate is very small, i.e. less than 100 people, then data will not be published as it could risk revealing individuals’ identities. This will be discussed in more detail in chapter 3. 

38.	In some instances, the data we will go on to discuss, will not meet your needs, and there will be occasions when you will require more specific data. In Part 2 of the toolkit, which will be published in Spring 2014, we will go on to discuss how you can collect your own data. 

39.	Using existing data, you cannot always get a perfect fit between the data you want and what data is available. However, there are ways to use available data as a proxy for the data that you want. Generally, this is when the data you want and the data you have is similar. For example, if data is not available for your community, try and look up a community that is similar to yours and use that instead. This is called using a ‘proxy’ (that is, the other community is a ‘proxy’ for your community). Alternatively, you can try using regional or national data as a proxy. 

Scenario 2: Fatima is in the final year of her degree and wanted to know what the labour market outlook was for students in her district, Tendring. Looking at the Tendring District Council webpage, she was able to find the council’s profile statistics. Although this supplied general labour market statistics, it did not have any figures for students. However, she was able to find these statistics for her region, East of England, and used this as a proxy.  

40.	However, please note that you must not misinterpret the data to make it fit your needs and it should be clear in your results that you are using proxy data.

41.	The UK Data Archive (link below) holds data on all the major surveys and will be the main source of information for a number of these themes. To access the data a subscription is required, if your organisation does not have one you can apply for one on the website. This subscription is free for charities and NGO’s but commercial organisations will have to pay a fee to access the data. Once subscribed you can search for and download the data you would like. However, you will need access to a statistical software package to both download and access the data. 
http://ukdataservice.ac.uk/ 

Disability

42.	There is a lot of data available on basic disability numbers, for example, the number of disabled people in Scotland, and the number of DLA claimants by local region. 

43.	The main source of this type of data is NOMIS (link below). NOMIS is a service provided by the Office for National Statistics (ONS) to provide access to the UK’s labour market statistics from a number of data-sources. It provides data at a national, regional and local level.  The ONS is also a good source of information. They manage a wide range of surveys and should always be the first port of call for any data you are looking for.
http://www.nomisweb.co.uk/ 

Hint: Comparisons with other areas, and in particular national data, can make your local level data more meaningful. For example, you can show whether the data for your area is better or worse that the national picture.

44.	NOMIS is easy to use and has a number of set-up assistants and user guides to direct you through the website and get the data you require. 

45.	The Life Opportunities Survey, is another source of good information. It is a longitudinal survey, (a type of survey where the same group of people are asked to fill in a survey repeatedly over a period of time) which explores disability in terms of the social barriers that people experience. The national findings of the survey are published on the ODI website (link below). 
https://www.gov.uk/government/collections/life-opportunities-survey

46.	However, if you wanted to conduct some of your own analysis you would have to download the dataset from the UK data archive. 
http://discover.ukdataservice.ac.uk/series/?sn=2000027 

Hint: Life Opportunities Survey variable name for region is ‘GOR’ and for Local Authority is ‘LA’.

47.	Please look at Annex A for a full list of useable data. 

Scenario 3: Sarah wanted to know the ethnic breakdown of disabled people in her local area, and her neighbouring areas. She knew a little about research so thought the Census may be a good source of information. After doing some research she came across the NOMIS website. Using the Wizard Query she was able to select that she wanted Census data (detailed characteristics). She then scrolled down the list of all the possible breakdowns she could get until she found the one she wanted – long-term health problem or disability by general health by ethnic group by sex by age.

Sarah then selected - what size of area she wanted to look at (regional or local authority etc), the age group, gender, general health, what ethnicity she wanted to look at and that she only wanted disabled people (by only selecting people whose day-to-day activities are limited a lot or a little).
 
Finally Sarah selected what format she wanted the data in (excel or a webpage) and got her data. 

She found the NOMIS website easy to use and was pleased with the data she received. From this she was able to see what the ethnic breakdown was in her own and neighbouring districts.

Sarah found out that many disabled people living in her local area were likely to speak Urdu. As a result, she made sure flyers and materials for an event she was organising were also written in Urdu. 

Education

48.	Schools are required to release a certain amount of information and data. From September 2012 all schools have to publish ‘key’ information. This includes details of the school’s policies on behaviour; charging; SEN and Disability provision; links to the schools Ofsted report; as well as the schools performance tables and details of the schools latest key stage 2 and 4 performances. 

49.	Local schools provide links to their results on their website. However, if you would like to study performance levels for a region or Local Authority or even nationally, this data is kept by the Department for Education (link below). 
https://www.gov.uk/government/publications?departments[]=department-for-education&publication_filter_option=statistics 

50.	The one thing that you need to be aware of when using this data is the use of Special Education Needs (SEN). Most schools do not know whether their pupils are disabled or not, as they are only required to keep a record if a pupil has a SEN (both with and without a statement). When using SEN data you should be careful when making comparisons to past data as there have been many changes in the way a pupil is defined as SEN.  

51.	Please look at Annex A for a full list of useable data. 

Scenario 4: Bill wanted to set up a support network for disabled people going through their GCSEs. He was putting together a business case to get the funding for this, and needed to know how many people were likely to turn up. To do this he went on the Department for Education website and using the search engine on the statistics page was able to get the GCSE pass rate for the local authority. This data showed the pass rate for children with and without SEN, and the number of SEN children. Although this did not tell him exactly how many disabled people went to school in that area, it provided him with an accurate basis which he could build upon, after talking to some schools in his local area. 

 Employment

52.	Labour market statistics for disabled people are readily available. The best source of this data is NOMIS (link below). Using the website you are able to get this data to a district or county level. The ONS also publishes monthly labour market statistics which shows the national level, which can be used as a comparison. 
https://www.nomisweb.co.uk/ 

53.	For those who are feeling a little more adventurous, the Labour Force Survey (link below) is primarily a cross-sectional survey (so every time it is run it is asked to a different group of people) of employment circumstances of the UK population. This has data on a wide range of employment topics from individuals who are not in work but would like to be, to hourly wage rates.  It is a quarterly survey, however, it is recommended to use the survey to make year-on-year comparisons. For example comparing the first quarter of 2010 with the first quarter of 2011. This is because employment patterns are usually ‘seasonal’ (for example, there tends to be more jobs available in seaside towns during the summer) so comparing different quarters (for example Q1 and Q3) is not comparing like with like.
http://www.ons.gov.uk/ons/about-ons/get-involved/taking-part-in-a-survey/information-for-households/a-to-z-of-household-and-individual-surveys/labour-force-survey/index.html 

54.	The survey is available to be downloaded from the UK data archive. 
http://discover.ukdataservice.ac.uk/series/?sn=2000026 

Hint: Labour Force Survey variable name for region is ‘GOVTOR’ and for Local Authority is ‘UACNTY’.

55.	Please look at Annex A for a full list of useable data. 

Scenario 5: David managed an employment support service in Brighton and was thinking of moving to Durham. He wanted to move his business with him. However, he was concerned that he may not get the required demand in Durham.

David used the NOMIS website to see what the unemployment rate was for County Durham and Brighton and Hove. He used the wizard query and selected Census data local characteristics, and economic activity by hours worked by long-term health problem or disability. David was then able to select the two local authorities he was interested in, to just look at disabled people (by only selecting people whose day-to-day activities are limited a lot or a little) and then select that he wanted to look at the employment rate.

The figures showed that there was only a small difference in the employment rates. So David, was able to use these figures to inform his decision about whether or not to move location.  

Income

56.	Data on income is harder to find than for some of the other themes. There is no specific survey, or government department dedicated to income policy or the gathering of income data. This is because income is linked to many different aspects of society.

57.	Data on income is mostly survey based. The Family Resources Survey, a cross-sectional survey, is the main survey on income data, and it is used for the Households Below Average Income (HBAI) publication which is released every year (link below). 
https://www.gov.uk/government/organisations/department-for-work-pensions/series/family-resources-survey--2

58.	National data can be accessed on the Department for Work and Pensions website (link below).
https://www.gov.uk/government/organisations/department-for-work-pensions/series/households-below-average-income-hbai--2 

59.	Unfortunately, local level data on the income of disabled people is not published online, although it is possible to calculate the data using the Family Resources Survey.  

60.	The survey, including the HBAI data, is available to be downloaded from the UK data archive.  
http://discover.ukdataservice.ac.uk/series/?sn=200017

Hint: Family Resources Survey variable name for region is ‘GCTREGN’ and for Local Authority is ‘LAC’.

61.	Another source of data is the Annual Survey of Hours and Earning. This is a survey that provides information about the levels and make-up of earning for employees. Although this does not take into account all types of income, it can be used as a proxy to compare areas, as the data can be broken down to Parliamentary constituency.  http://www.ons.gov.uk/ons/rel/ashe/annual-survey-of-hours-and-earnings/index.html 

62.	Please look at Annex A for a full list of useable data. 

Health and Wellbeing

63.	Data available on health and wellbeing is mostly administrative data (data that has been collected as part of running a business). This is available from the Health and Social Care Information Centre (link below). Using this website you can search for the specific data you require. At times, the website is not the easiest to use, but it does hold a lot of useful information. The best source of local level data on this website is the Adult Social Care Outcomes Framework. This is a set of outcomes that the Department of Health is using to monitor adult social care in England. Data is available by Local Authority. A number of these outcomes are on disability related issues for example the proportion of adults with learning disabilities in paid employment.
http://www.hscic.gov.uk/searchcatalogue 

Scenario 6: Miguel wanted to know how carers are being included in the health care of the individual(s) they are caring for. Looking on the internet he came across the Adult Social Care Outcomes Framework. This framework had a number of indicators on carers. The main indicator he was interested in was the ‘proportion of carers who report that they have been included or consulted in discussions about the person they care for’. The report noted that the data was kept on the Health and Social Care Information Centre (HSCIC). 

Looking through the HSCIC website, Miguel struggled to find the data. Eventually, he clicked on the Official Statistics Report link on the Adult Social Care Outcomes Framework page of the HSCIC, and found the data (link below).  Using this webpage Miguel was able to see what the figures were for England, his region and his local authority. 
http://www.hscic.gov.uk/catalogue/PUB12610 

64.	Another source of data is Public Health England, who are an executive agency of the NHS. They have their own data on their website, which is mostly on vaccinations (link below).
https://www.gov.uk/government/publications?departments[]=public-health-england&publication_filter_option=statistics

65.	However, they also have their own Public Health Outcomes Framework. This is mostly local authority data which they use to understand how well public health is being improved and protected. As part of this they have a Public Health Outcomes Framework data tool, which can be found at the link below. The tool enables you to view the data for your local authority and compare it with other authorities in the region. A number of these outcomes are related to disabilities, for example the proportion of adults with a learning disability who live in stable and appropriate accommodation.
www.phoutcomes.info

66.	There are a number of surveys which record data on health and wellbeing, like the ONS Experimental Wellbeing Survey which is a cross-sectional survey (which is associated with the Annual Population Survey) and Understanding Society which is a longitudinal survey.  

Hint: ONS Experimental Wellbeing Survey variable name for region is ‘GOR’. In Understanding Society the variable name for region ends with ‘gor_dv’.

67.	These surveys are available to be downloaded from the UK data archive.  
http://discover.ukdataservice.ac.uk/series/?sn=200002 
http://discover.ukdataservice.ac.uk/series/?sn=2000053

68.	Please look at Annex A for a full list of useable data. 

Scenario 7: Kate was interested in investigating health outcomes for people with mental health problems, for her university dissertation. She was looking on the Department of Health website when she came across the Adult Social Care Outcomes Framework. The framework’s focus is on promoting people’s quality of life and experience of care. Looking through this she found that two of the outcome measures were about mental health, and that a number of the other measures could provide a breakdown by impairment type which included mental health (like social care related quality of life).

Using the Health and Social Care Information Centre website, she was able to get the data for these outcome measures and used them to do a comparative analysis on the nine geographical regions of England.

Transport

69.	Data available on transport is survey based. The Department for Transport gathers a lot of this information. One of the surveys they run is the National Travel Survey. This survey has a lot of information including the number of trips individuals take broken down by local area. However, in order to find out if respondents are disabled or not, it is necessary to download the data from the UK data archive. 
https://www.gov.uk/government/organisations/department-for-transport/series/national-travel-survey-statistics 
http://discover.ukdataservice.ac.uk/series/?sn=2000037 

70.	Another source of information is Passenger Focus. They run two useful surveys, the Bus Passenger Survey and Rail Passenger Survey. The Bus Passenger Survey consults with more than 20,000 passengers a year, and measures passenger’s satisfaction with their local bus service. As well as publishing a report, the data is available to analyse yourself online (link below). The chart maker allows you to pick questions from the survey and compare disabled and non-disabled people responses by region, however, please note if the sample sizes are too low the data will not be provided. https://manager.dapresy.com/manager/Storyboard/RHViewStoryBoard.aspx?RId=%C2%B6&RLId=%C2%B5&PId=%C2%B1%C2%B1%C2%B3%C2%B9%C2%B4&UId=%C2%B4%C2%B1%C2%B8%C2%BA%C2%BD&RpId=6 

71.	The Rail Passenger Survey is very similar in format, this survey consults with around 50,000 passengers a year to get their opinions of their train services. This data is also available to be analysed yourself, through the link below. This again, allows you to pick survey questions and compare disabled and non-disabled people responses by region.
http://www.npsreportal.org.uk/ 

72.	Please look at Annex A for a full list of useable data. 

Scenario 8: Emma was trying to gather some data for her campaign about disabled people and the transport difficulties they face on a day-to-day basis. Searching through the internet she found the Rail Passenger Survey.

Using the NPS analysis tool (Reportal) report function she was able to see if disabled people felt that their needs were being met during their rail journey, by different breakdowns (for example age and ethnicity) for her region. As well as finding out disabled people’s satisfaction levels with train arrangements to get on and off the train.

Using this Emma was able to target her campaign on the sections where the data showed improvement was needed and had the data to back-up her claims.

Housing

73.	Data available on housing is mostly from the Department for Communities and Local Government (DCLG). The data is a mixture of survey and administrative data. The Department regularly publishes Local Authority data, which can be accessed at the link below, on topics such as housing finances and housing waiting lists. However, this data is not split by whether the household has a disabled member or not. 
https://www.gov.uk/government/organisations/department-for-communities-and-local-government/series/local-authority-housing-data 

74.	Some Local Authorities also publish these figures themselves. So it is always best to ask your Local Authority first for this data, as they were the ones who supplied it to DCLG.  

75.	The main housing survey run by DCLG, is the English Housing Survey. This is a cross-sectional survey, which runs every year, and collects information about people’s housing circumstances and the condition of their housing.  
https://www.gov.uk/government/organisations/department-for-communities-and-local-government/series/english-housing-survey 

Hint: English Housing Survey variable name for region is ‘GOREHS’.

76.	Although a lot of the data provided on the DCLG website is broken down to a local level, it does not state whether the household has a disabled member. However, it is possible to calculate this using the English Housing Survey data, which is available to be downloaded from the UK data archive. 
http://discover.ukdataservice.ac.uk/series/?sn=200010 

Hint: When downloading the data, it is useful to also download the user guide. This will explain what is in the dataset and help you identify the variables you need for your analysis.  

77.	Please look at Annex A for a full list of useable data. 

Scenario 9: John lives in the London Borough of Camden, and wanted to know what his council does for disabled people. Going onto the council website John came across a link for the Camden Data website.

Looking through the Camden Data website John came across the Evidence base for Camden’s Housing Strategy. This evidence base was put together to inform the council’s housing strategy 2011-2016.  
 
The evidence base provided trends for the people in Camden, their housing needs and the links between housing and wellbeing. John found out just how many disabled people lived in Camden and the number of people who needed support to stay in their homes. The evidence base also showed the council estimates of what these figures will be in 2020.

Other disability data

78.	General Census data is accessible using NOMIS (link below). Using the website you can access national, regional and local level data for a range of topics. This website also has data from a wide range of other surveys, so can help with a large range of population questions, for example, employment rates and the number of benefit claimants.  
http://www.nomisweb.co.uk/ 

79.	For more specific research questions the best place to look is the ONS website. On the website, link below, you can search for the data you require. This includes disability data like crime statistics and the number of people in communal establishments. 
http://www.ons.gov.uk/ons/datasets-and-tables/index.html 

80.	Please look at Annex A for a full list of useable data. 

Scenario 10:  Robert saw a recent article saying that reports of disability hate crime was rising. This led him to wonder what the hate crime figures were for his area. He checked on the ONS website and although they had a lot of other figures, he could not find any figures on hate crime. So he looked on the gov.uk website and found the data on the Home Office statistics webpage. 

The data shows the different types of hate crime, including disability hate crime, by police force area – county. This enabled him to compare the current and past figures for his county.

81.	In order to develop the toolkit, in particular Part 2, we would like to know what analysis you would be interested in. Please send your ideas to fulfilling.potential@dwp.gsi.gov.uk

82.	We will be looking into how we all can share data more widely.

Chapter 3 – Using data

How to analyse data 

83.	As previously discussed there are different sources and types of data, all of which provide different kinds of information. 

84.	It is important to select the correct type of data for your needs. Each type has their own uses. It is important to think about which type of data you need to answer the questions you have.

Sources of data

85.	There are two main sources of data, research and administrative data. The following section will go through these data sources and explain the main ways to analyse them.

86.	Research data. There is no set way of analysing research data, as it is a source of data rather than a type of data, in other words it is a way of grouping types of data. As such the qualitative and quantitative (either cross-sectional or longitudinal) sections below will set out how to use research data.   

87.	Administrative data.  As discussed previously administrative data is information that is collected for administrative purposes. The way it is analysed depends on how the data was collected, how it is stored and how many variables you have. If the data is collected at given intervals from the same individuals and is stored in a way that you can tell when the data was collected (for example March 2012) – then you can measure this data longitudinally. If the data is large enough, but cannot be measured longitudinally, then you can analyse the data using cross-sectional techniques. It is often useful to analyse administrative data using descriptive statistics. This lets you condense a lot of information into one simple to understand table. 

88.	An example of using descriptive statistics to analyse administrative data is below. 

Example 2: Mark needs to demonstrate client satisfaction for a new service. He therefore designs a client feedback form. This ensures that, as part of the service, clients are asked a series of questions about how they found the service. From this data, he was able to report the percentage of people who felt the service had helped them and who would recommend it to others.  

89.	Administrative data is normally quantitative: that is, it consists mainly of numbers. That means it should be analysed using quantitative data techniques. You should consider how the data was collected in determining what quantitative technique to use

Types of data

90.	There are five main types of data: qualitative, quantitative, cross-sectional, longitudinal, and evaluations. The following table provides a summary of what type of statistical technique to use for each of these types of data.

 	Descriptive statistics	Means testing	Correlation	Regression	Segmentation analysis	Qualitative thematic analysis	
Qualitative data					X	X	
Quantitative Cross-sectional data	X	X	X	X	X		
Quantitative Longitudinal data	X	X	X	X	X		
Quantitative Evaluation data	X	X	X	X			
Qualitative Evaluation data					X	X	

91.	The following section will go through each of these data types and explain the main ways to analyse them.

92.	Qualitative data. This is very different to all the other types of data, as unlike other sources the individuals’ responses are words rather than numbers. The way this data is analysed is by reading through the data, for example the transcripts of the interviews/focus group. You make notes of individual themes that are mentioned in the data, then draw these together into overarching themes.

93.	An example of qualitative research is the Equality and Human Rights Commission Research Report Opening up Work (Adams and Oldfield 2012). More information on this can be found in Annex D.

94.	The following is a link to a paper written by the University of Wisconsin which goes through the process of analysing qualitative data in more detail:
http://learningstore.uwex.edu/assets/pdfs/g3658-12.pdf

95.	Quantitative data. There is no set way of analysing quantitative data. Most data sets are cross-sectional or longitudinal. Below, is more detail about these two types of data sets. 

96.	Cross sectional quantitative data. This is when the data provides a picture of what society looks like at a moment in time. The advantage of cross-sectional research is that you can apply most statistical techniques to it, from regression analysis, to descriptive statistics (these statistical techniques will be explained later on). These allow you to look at the features of your target group and explore their relationships. An example of cross-sectional data is Opinions and Lifestyle Survey. More information on this can be found in Annex D. 

97.	Further information on how to analyse cross-sectional data can be found here:
http://www.slideshare.net/sumizin/3-cross-sectional-study 

98.	Longitudinal quantitative data. As previously stated longitudinal data looks at changes over time for specific individuals. The first data received (for example year 1) can be analysed like cross-sectional data. However, from then on the way to analyse the data is to look at the changes since the previous year. For example, when you receive year 2 data you can compare it with year 1, and when you get year 3 you can compare it with years 1 and 2. This enables you to see if there have been any changes over the period. The way to analyse this is through means testing (this will be explained later on). 

99.	Example 3 below, shows how someone collected administrative data in a way that meant that it could be analysed in a longitudinal way.

Example 3: Clara runs an organisation that helps people cope with mental health problems and wants to know how much people improve after using the service. She asks clients to fill in a questionnaire designed to measure how much they are suffering from their symptoms when they first access the service and then again at the end. By comparing the two, she can see how much people’s mental health improved while using the service. 

100.	Another example of longitudinal data is the Life Opportunities Survey. More information on the Life Opportunities Survey can be found in Annex D.  However, please note, so far there has only been two waves of the Life Opportunities Survey, so it is not possible to conduct any real longitudinal analysis on this. Generally you need at least 3 or 4 years worth of data before you conduct any longitudinal analysis. 

101.	Further information on how to analyse longitudinal data can be found here:
http://faculty.washington.edu/heagerty/Courses/VA-longitudinal/private/LDAchapter.pdf

102.	Evaluation data. This is when the effects of a policy/change are investigated. Data for evaluations is either collected by doing your own research or using existing data, either quantitative or qualitative. Therefore the way you analyse evaluation data is dependent on the data collection. For example, if you wanted to see if a policy has made a change to your community by speaking to people, this will be a qualitative piece of research so should be analysed as qualitatively.

103.	The only exception to this is cost-benefit analysis. Cost-benefit analysis is when you assign a monetary value to the benefits and costs of carrying out a project or policy and then use these values to see if the project is cost effective or not. Simply put it is the benefits of the project minus the costs of the project. The complex part of this is assigning a monetary value to everything. This is difficult as how do you assign a value to an increase in positive attitudes or happiness? A lot of work has been done on assigning values to everyday benefits and costs. So it is worthwhile doing some research before you start, to see what other organisations have used. However, some costs and benefits will have a greater value to your organisation than others, so make sure the values you use reflect your organisation. The overall aim is to have a positive value when costs are taken away from benefits, if not then the project/policy is not cost-effective.

104.	Further information on how to analyse evaluation data can be found in the Magenta Book:
https://www.gov.uk/government/publications/the-magenta-book 

Common types of analysis

105.	The following section will go through the main types of analysis. For more information about the techniques and the main ways to use them please see Annex D.

Quantitative analysis

106.	Descriptive statistics. This is a way of summarising large amounts of data, as it looks at the make up of your target group. The main use of descriptive statistics is to answer the questions of ‘how many’ and ‘what proportion’. 

107.	Means testing. This compares the differences between groups of people. It is often used in evaluations to compare a treatment group (people who have received a policy change) with a control group (people who have had no policy change). 

108.	Correlation. This looks at whether two variables are linked or related in some way. 

109.	Regression. This looks at the relationship between a number of variables. What makes it different from correlation is that it can tell how related the variables are. 

110.	Segmentation. This is a way of dividing up a market/society to identify trends within it and create a profile of your target group. 

Qualitative analysis

111.	Qualitative thematic analysis. This is a way of dividing data/information into themes. 

Evidence collection

112.	Evidence synthesis. This involves combining evidence from multiple studies in an organised way. The main way of doing this is the qualitative approach, which is also called realist synthesis.  

How to interpret data

113.	After producing the analysis it is important to know how to interpret it. Unfortunately, there are many ways to misinterpret results or misuse statistics. Some of the pitfalls to avoid are:
•	Not knowing the subject area. It is important that you are aware of the context of your analysis, changes to policy or the introduction of new variables can significantly impact the picture of society. So the changes you see in your analysis may not be down to the reasons you suspect. For example, legislation around SEN has changed a lot over the past ten years, it is important to know what these changes are in order to understand the results. It may not be reasonable to compare your current data with past data.
•	Reading too much into the findings. It is important that when analysing data, you only report what the data is saying. It is very easy to use your knowledge of the area to give more meaning to the data, but it is important that when doing this there is a distinction between your knowledge and the data. You cannot say that the data is backing up your views if it is not 100% doing so. 
•	Making sweeping comments. This is very similar to the above pitfall, as it is again about understanding what the data is actually saying and only reporting this. When trying to interpret results, and simplify what it is saying, it is possible to lose the real meaning of the data. As such, you need to be very careful when interpreting the results.
•	Knowing your variables. This is very important in quantitative analysis. It is essential that you understand what variables you are using. What are they really saying? For example, not all surveys use the same definitions, one survey may use one definition of disability and other survey could use another definition, therefore you couldn’t compare results from those two surveys. More information on the different definition of disability can be found in Annex B. Additionally certain questions on a survey are only asked to a selected group of people, for example, a question on what is your impairment could be asked to all survey respondents or to only disabled respondents. 

114.	Analysis is precise – each finding tells you one thing – so you need to be careful not to misuse data. It is important to know: what questions the respondents were asked; the type of data collected; the variables used; and how it was analysed. This will enable you to draw accurate findings. 

115.	There are many different ways of making your results more meaningful. A key way of doing this is by using comparisons. Drawing comparisons can put your analysis into context, it brings in the wider picture and it becomes easier to understand. The comparisons you can do are:
•	Compare your community data to the national or regional average;
•	Compare your results to past results, to get a view of how the issue/topic has changed over time;
•	Compare your results with other communities near you; and
•	Compare your results with other communities with similar characteristics to your own. 

116.	When interpreting data there are some rules that need to be followed. Each data-set has their own rules so it is important to look these up before using any data.
 
117.	It is important to consider confidentiality. When an individual takes part in any type of data collection, be it a survey, an interview, or having their administrative data collected, they are given a guarantee that the information they are providing is confidential. It is our role as analysts of the data to ensure that this is upheld when conducting the analysis. 

118.	When analysing qualitative data you must be especially careful that nothing that could identify the respondent is published in the final report.

119.	The same applies for quantitative analysis, but this is slightly easier to police. The basic rule is that:
•	 You should have a minimum sample size (the number of respondents) of 1,000 people.
•	At least 100 people need to have answered the question. 
•	At least 100 people need to be in every sub-group you are measuring, so in the table below, each of the blue or # cells need to total at least 100. 
•	If a question has more than one type of response (for example a question on gender, or marital status etc) each type of response should have at least 5 people in it, so in the table below each pink or * cell needs the total to be at least 5. 

Table 3.2. Number of disabled people in the UK by age	
 	Disabled people	Non-disabled people	
0-16 years	*	*	
16-25 years	*	*	
26-35 years	*	*	
36-45 years	*	*	
46-55 years	*	*	
56-64 years	*	*	
65 years and over	*	*	
Total	#	#	

120.	However, as stated previously different data-sets have different rules, so please check these before doing any analysis.    

Chapter 4 – Evaluation of the Community Data Toolkit

We have, in this document, given an overview of what makes data and how it can be used.  We now need to evaluate its use and benefits.  In effect this is the final and ongoing example of the use of data in this document.

This document has been discussed with stakeholders, circulated to a wide audience and made available on the internet.  Hopefully, it will have been read by a variety of people and organisations who may be considering undertaking their own data analysis, whether to, identify where services could be improved, prepare a business case for project funding or, evaluate whether a service is delivering results.  We also need to know whether this document has met the needs of its readers/users.  Below is a short set of questions. Please can you email your responses to these questions to fulfilling.potential@dwp.gsi.gov.uk or post them to: 

Office for Disability Issues
Department for Work and Pensions
CaxtionHouse
Tothill Street
London
SW1H 9NA

We will regularly review the results and prepare a short evaluation which we will place on line.  We will also be reviewing the results to ensure that the toolkit meets the needs of users, and where appropriate will make updates available.

Remember when completing the evaluation that this is Part 1 of the toolkit, Part 2, which will deal with the creation of your own surveys and the collection of your own data will be available spring 2014.

Evaluation Questions

1.	How did you become aware of the Community Data toolkit?

2.	How clear did you find the language (very clear, clear, not clear)? Please also provide any comments. 

3.	How useful did your find the toolkit (very useful, useful, not useful)?  Please also provide any comments.

4.	Have you undertaken any data analysis as a result of reading the toolkit? If so:
•	Please describe your analysis and indicate if you are willing to share your findings with others?
•	Would you in the future be prepared to write a short case study that could be published, and used to help others?

5.	Do you feel that there is something missing from the Toolkit?

6.	Do you have any other comments you wish to share?

Finally, please provide name, organisation and contact details.

Annex A - Links to data

Search Tools
Community Insight is a web-based tool which allows non-experts to explore social indicators for specific geographical areas. The tool is only available on a subscription basis. However, you can sign up for a free demo. The full subscription is £5,000 plus VAT.
http://www.communityinsight.org/

Local Authorities
Camden Local Authority has a webpage where it keeps all its analytical data. It has census data, Children and Young People’s Profile and their Joint Strategic Needs Assessment for Health and Social Care among other things.
http://www.camdendata.info/Pages/Home.aspx

Other Local Authorities have similar webpages or they have this type of information incorporated into their main website. It is always best to check your local authority website before conducting any analysis yourself as it may already be done for you. If you cannot seem to find any information, then do no hesitate to ring the Local Authority helpdesk, as they can normally direct you to the correct webpage. 

Local Government Association
They have a tool ‘Local Government Inform’ which is an online service which allows you to access, compare and analyse data. LG inform allows you to look at reports at a Local Authority level, while with LG inform plus you can look at data for your ward.
http://lginform.local.gov.uk/ 
http://about.esd.org.uk/ 

NOMIS
NOMIS is a service provided by the ONS to provide access to the UK’s labour market statistics from a number of data-sources. It provides data at a national, regional and local level.

At a Local Authority level it has data on; resident population, employment and unemployment; economic inactivity; employment by occupation; qualification; earning by residence; out-of-work benefits; jobs; jobcentre plus vacancies; and VAT registered businesses.

Specifically on disability it is possible to get the number of working age disabled people who are claiming a benefit by region and Local Authority. It is also possible to get Census data on the number of individuals who are disabled or have a long term illness/condition. This Census data can also be broken down by region and local authority, as well as by ethnicity, gender, age, religion and general health.

An example of using NOMIS can be found in chapter 2, scenario 3.
http://www.nomisweb.co.uk/ 

GP Patient Survey
This is a survey which asks people about their experiences of their local NHS services. As such data is available at a local level. One of its useful tools is the ability to search for your local practice and compare it to other local practices within a 5 mile radius. 
http://www.gp-patient.co.uk/results/ 

Child and Maternal Health Intelligence Network
They provide information to support decision making. They have interactive maps relating to child and maternal health, child health indicators and provide assistance on producing local reports.
http://www.chimat.org.uk/ 

Active People Interactive
Sport England run a survey called the Active People Survey. The survey is the largest survey of sport and active recreation in Europe, and is used to monitor and understand trends in sport. They have just launched an interactive tool to analyse this data. This tool allows you to view sport trends for your local area.  
http://activepeople.sportengland.org/ 

Government Departments

Data.gov.uk
This website contains a large amount of current and past data. On the website you can search for the data you would like or use the interactive maps to see what data is available for your community.
http://data.gov.uk/ 

DWP Tab Tool
This is good tool to get figures on a benefit or scheme that you are interested in. Using the options provided you are able to get figures for your region, local authority or parliamentary constituency. However, please note, if there are not enough individuals in a category the data will not be provided. 
http://tabulation-tool.dwp.gov.uk/100pc/ 

Office for National Statistics (ONS)
The ONS published a vast amount of statistics on topics from labour market, to mortality rates. A large proportion of this data is available at either Local Authority or regional level. 

The following links are of data at local/regional level from the ONS. However, this list can never be exhaustive, the ONS changes the data it collects regularly, so it would be wise to check and learn how to use the ONS website.

General heath. The ONS provides statistics on self-reported sickness by region and gender. This provides information on the number of people with a long-standing illness/disability, or a limiting long-standing illness/disability.
http://www.ons.gov.uk/ons/taxonomy/index.html?nscl=Life+Expectancies#tab-data-tables 

Labour market statistics. The ONS provides the Labour Market Status of disabled people. Even though, they do not break this down by region, it is useful to have, so that you can compare your region with the national figure.  
http://www.ons.gov.uk/ons/rel/lms/labour-market-statistics/index.html 

Data on disability. This includes census local characteristics. The ONS has data on the number of people with a long-term health condition or disability broken down by Local Authority. 
http://www.ons.gov.uk/ons/taxonomy/index.html?nscl=Disability+and+Self-reported+Health 

Crime statistics. The ONS published their crime statistics for each Local Authority. 
http://www.ons.gov.uk/ons/taxonomy/index.html?nscl=Crime+in+England+and+Wales

Marriages, Cohabitations, Civil Partnerships and Divorces. The ONS publishes Marriages, Cohabitations, Civil Partnerships and Divorces for England and Wales, broken down to a district level.
http://www.ons.gov.uk/ons/taxonomy/index.html?nscl=Marriages%2C+Cohabitations%2C+Civil+Partnerships+and+Divorces

Income and wealth. ONS publishes data on Personal Income and Wealth. This includes the number of people on a disability benefit by region.
http://www.ons.gov.uk/ons/taxonomy/index.html?nscl=Personal+Income+and+Wealth 

County profiles. The ONS releases region and county profiles monthly, on the number of DDA disabled people across the UK by region.
http://www.ons.gov.uk/ons/rel/regional-trends/region-and-country-profiles/index.html

Civil service statistics. This provides the number of disabled people employed by the civil service by their grade and their geographical region.
http://www.ons.gov.uk/ons/rel/pse/civil-service-statistics/index.html

UK Data Archive
The UK Data Archive has the largest collection of digital data in social sciences and humanities in the UK. The archive has information and data on a wide range of secondary data including government surveys, international macrodata, qualitative studies and census data. Via the UK Data Service you can look up what the key data sources are, or even explore the data sources by theme. It is a good starting point for looking for what data is available – even if you don’t intend to get the data from them. To access the data a subscription is required to the UK Data Archive. This is free for charities and NGO’s but commercial organisations will have to pay a fee. Additionally, a statistical software package is required to both download and access the data. 
http://data-archive.ac.uk/  

Published reports

Many non-government organisations conduct surveys and analysis on disability, and can be a great source of information. Below are links to a selection of reports and articles that have been published recently. 

The Other Care Crisis. The Other Care Crisis is a report published by Scope, Mencap, The National Autistic Society, Sense and Leonard Cheshire Disability. The report is about making social care funding work for disabled adults. 
http://www.scope.org.uk/Scope/media/Documents/Publication%20Directory/The-other-care-crisis-1.pdf?ext=.pdf

Disabled People and Financial Wellbeing. A Scope commissioned report by Ipsos MORI on disabled people and their financial wellbeing. 
http://www.scope.org.uk/Scope/media/Documents/Publication%20Directory/Credit-and-Debt.pdf?ext=.pdf   

Disability Poverty in Wales. This is a report conducted by Leonard Cheshire Disability report on economic hardship in Wales.
http://www.leonardcheshire.org/sites/default/files/Disability%20Poverty%20in%20Wales.pdf

Discretionary Housing Payments. Papworth Trust with support from the National Housing Federation published findings of their survey on Discretionary Housing Payment. 
http://www.housing.org.uk/media/press-releases/disabled-people-cutting-back-on-food-and-bills-to-pay-bedroom-tax 

Safety and Security for Disabled People. Equality and Human Rights Commission report on Disabled People’s experiences of targeted violence and hostility. 
http://www.equalityhumanrights.com/key-projects/good-relations/safety-and-security-for-disabled-people/summary-of-the-research-findings/ 

Rights and reality. Leonard Cheshire Disability report of Rights and reality in 2010. This is on disabled people’s experiences of accessing good and services.
http://www.leonardcheshire.org/who-we-are/publications/latest-publications-download/rights-and-reality-disabled-people%E2%80%99s#.U8TyNKx2NU4  

Ending 15-minute Care. This is a Leonard Cheshire Disability report on ending 15-minute care.
http://www.leonardcheshire.org/sites/default/files/15%20min%20care%20report%20final.pdf

Independence, Choice and Control. A Leonard Cheshire Disability report on Independence, Choice and Control.
http://www.leonardcheshire.org/sites/default/files/Independence,%20Choice%20and%20Control.pdf

Dad and Me. Netbuddy and Scope published a report on the issues that face UK father carers.
https://www.scope.org.uk/About-Us/Media/Press-releases/June-2012/Fathers-with-disabled-children-feel-marginalised

Paralympic legacy. A Scope conducted a poll on the Paralympic legacy. 
https://www.scope.org.uk/About-Us/Media/Press-releases/August-2013/Paralympics-legacy-in-balance-as-attitudes-fail-to 

Annex B - Definition of disability 

When using existing data, it is important to be aware that not all data uses the same definition of disability. In research individuals can simply be asked ‘are you disabled’, this is called a self-declaration, or they can be asked a series of questions and the responses are then used to calculate if the individual is disabled. 

The later option is what we will be going on to discuss. Using questions to calculate if someone is disabled is the approach generally used in surveys. The problem is that not all surveys use the same set of questions.

During this toolkit we have mentioned 6 major surveys, for each of these surveys here is the definition they use or used in 2012:

Family Resources Survey
They are currently using the Disability Discrimination Act definition, questions below. 
1.	Do you have any long-standing illness, disability or infirmity? By long-standing I mean anything that has troubled you over a period of at least 12 months or is likely to affect you over a period of at least 12 months. 
2.	Does this physical or mental illness or disability (Do any of these physical or mental illnesses or disabilities) limit your activities in any way?
If respondents answer yes to questions 1 and 2 then they are defined as disabled in accordance with the Disability Discrimination Act.

However, the FRS have changed their questions to be in-line with the Equality Act definition of disability. 2012-13 data will be the first year this definition is used. This definition will be discussed later.

Life Opportunities Survey
Disability Discrimination Act definition:
1.	Do you have any long-standing physical or mental impairment, illness or disability? By long-standing I mean anything that has affected you over a period of at least 12 months or that is likely to affect you over a period of 12 months?
2.	Does this/do these health problems or disabilities mean that you have substantial difficulties with any of these areas of your life? Moving; Lifting; Hands; Bladder; Speech; Learn; Danger; Balance; other; none.
If respondents answer yes to question 1 and not ‘none’ in question 2 then they are defined as disabled in accordance with the Disability Discrimination Act.

Labour Force Survey
Since Q2 2013 the LFS have been using the Equality Act definition of disability. This definition will be discussed later.

ONS Experimental Wellbeing Survey
They are currently using the Disability Discrimination Act definition, questions below. 
1.	Do you have any health problems or disabilities that you expect will last for more than a year?
2.	Do these health problems or disabilities, when taken singly or together, substantially limit your ability to carry out normal day to day activities? If you receiving medication or treatment please consider what the situation would be without the medication or treatment?
If respondents answer yes to questions 1 and 2 then they are defined as disabled in accordance with the Disability Discrimination Act. 

However, they have changed their questions to be in-line with the Equality Act definition of disability. 2013-14 data will be the first year this definition will be fully used. This definition will be discussed later.

Understanding Society
Disability Discrimination Act definition:
1.	Do you have any long-standing physical or mental impairment, illness or disability? By long-standing I mean anything that has troubled you over a period of at least 12 months or that is likely to trouble you over a period of at least 12 months.
2.	Does this/do these health problem(s) or disability(ies) meant that you have substantial difficulties with any of these areas of your life? Moving; Lifting; Hands; Bladder; Speech; Learn; Danger; Balance; other; none.
If respondents answer yes to question 1 and not ‘none’ in question 2 then they are defined as disabled in accordance with the Disability Discrimination Act.

English Housing Survey
2011-12 data is uses the Disability Discrimination Act definition of disability, questions used below. 
1.	Do you have any long-standing illness, disability or infirmity - by long-standing I mean anything that has troubled you over a period of time or that is likely to affect you over a period of time?
2.	Does this illness or disability (Do any of these illnesses or disabilities) limit (your/names) activities in any way?
If respondents answer yes to questions 1 and 2 then they are defined as disabled in accordance with the Disability Discrimination Act.

However, from 2012-13 the English Housing Survey has been using the Equality Act definition of disabled people.

Equality Act definition
On the positive side the ONS recently came up with a set of questions for surveys to use to calculate if an individual is disabled. These ‘harmonised’ questions show whether an individual is disabled in accordance with the Equality Act. The relevant questions are:

•	Do you have any physical or mental health conditions or illness lasting or expected to last 12 months or more?
Yes; No
•	Does your condition or illness / do any of your condition or illnesses reduce your ability to carry-out day-to-day activities?
Yes a lot; Yes a little; No not at all

If a respondent selects ‘yes’ to questions 1 and either ‘yes a lot’ or ‘yes a little’ to question 2 they are defined as being disabled in accordance with the Equality Act.  

Below is the link to the ONS document. 
http://www.ons.gov.uk/ons/guide-method/harmonisation/primary-set-of-harmonised-concepts-and-questions/long-lasting-health-conditions-and-illnesses--impairments-and-disability.pdf 

All major surveys will be adapting their questionnaires in order to include these questions, or a variation of the question. This means that by 2013-14 the major surveys should all use the same definition of disabled people – in accordance with the Equality Act. 

 

Annex C – Types of data

Research data. This is data that has been collected from a number of individuals in an organised way because an organisation or individual want to know something. Research data can also be called survey data. 

The most common way research data is collected is by using a questionnaire. There are many types of research data, from feedback forms to large government surveys. 

Research data is often used to measure real things/issues. However, it can also be used to collect other topics, like people’s opinions, attitudes, feelings and values about a given issue.

Advantages
•	The data is easy to use
•	Gives you an idea of the proportion of people who have similar views or fall into specific groups

Disadvantages
•	Survey bias – not all people complete questionnaires. Could those who do not answer be different to those who do? This is called survey bias.
•	Cannot use research data to ask why or how questions
•	Individuals may not be responding truthfully

Administrative data. This is information which organisations collect as part of running their businesses. This makes it different from ‘research data’, which is gathered because the organisation wants to know something. 

Administrative data should be used when you need hard facts, or when you want to measure a particular group or sub-group. 

Advantages
•	Data is wide ranging data 
•	Historical data is normally available
•	Data is updated regularly
•	Administrative data does not have as much survey bias
•	Data includes a lot of people who do not normally respond to surveys
•	Data can be linked with other data sources – to get a better data set

Disadvantages
•	Data sometimes lacks background information 
•	There are strong data protection issues
•	A researcher is not involved when the data is collected. So not all of the data is collected in a way that is usable

Qualitative data. This is information that has been collected through conversations with an individual, it is ‘a conversation with a purpose’. These conversations can vary in their formats from: the researcher having an idea of what questions they would like to ask the person taking part (this is called structured interviews); to the researcher having no idea of the detail, just knowing the broad subject area the questions will be on (this is called non-structured interviews). 

The main ways qualitative data is collected are; through interviews (which could be structured, semi-structured or non-structured), focus groups (where questions are asked to a group of individuals), and participant observation (when the researcher spends time with the individual/group to learn how they live their lives). 

Qualitative data is very important when trying to develop a deep understanding of an issue. It enables us to measure the ‘why’ and the ‘how’ questions, for example, ‘why do you feel this way’ and ‘how did this make you feel’.  These types of questions enable you to go beyond the surface and look at the wider and deeper issues.

Advantages
•	Provides depth and detail 
•	Encourages people to expand on their answers
•	Can be used to explain quantitative data – why a response was given

Disadvantages
•	Has a smaller sample size, as it is costly and time consuming 
•	Cannot use individuals’ responses and apply it to anyone else due to the small sample size. For example, if three women answer a question with the same response you cannot say all women think this way. 
•	Cannot use it to carry out comparisons, as individuals can respond to a question in many different ways
•	The collection is dependent on the skill of the researcher. If the researcher is unskilled then the data collected may not be as strong as it could be.

Quantitative data. This is data that can be measured using numbers. It is normally data that has been collected using a questionnaire. Quantitative data is normally viewed as the opposite to qualitative data. Where qualitative data looks at the detail, quantitative data looks at the bigger picture. An example of quantitative data is the census while an example of qualitative research would be a focus group (this is when a group of people come together to discuss a topic). There are two main types of quantitative data: cross-sectional and longitudinal. 

Quantitative data should be used when you want to conduct some statistical analysis. 

Qualitative and Quantitative data are at their best when used together. For example, using quantitative data to find what the general issues are and then qualitative data to delve into these issues, or vice versa using qualitative research to find an issue and how it affects people and using quantitative data to see how common the issue is.

Advantages
•	Allows for a broad study, will a larger sample size 
•	It is objective. Human feelings are removed from the data
•	The survey can be repeated. So data can be compared to past data if using the same survey

Disadvantages
•	Data is restricted to numbers, there is no detail 
•	Survey bias – those who do not complete the questionnaire could be different to those who do
•	Often responses are a best fit and are not a true representation of an individual’s feelings.
•	If respondents were not selected randomly or if the people selected do not reflect society, then you cannot apply your results to society. The selected respondents need to mirror society, so there needs to be a mix of ages, gender, ethnicity, geographical locations and income.
  
Cross sectional data. This is a form of quantitative data. It is numeric data collected using some form of questionnaire. It can be a one off or a repeated survey. What makes it different to longitudinal data (another form of quantitative data) is that every time a survey is asked, it is asked to a different group of people. This provides a picture of society for a specific point in time. 

Cross sectional data should be used when you want numerical data that you can apply to society or a particular group of people.

Advantages
•	The data is easy to use
•	Ability to have a large sample size 
•	Analysis of the data is simpler than other data types for example, longitudinal
•	Data can be used to talk about society or a particular group of people (if sample size is large enough). For example, if the majority of disabled people in a survey claim PIP or DLA we can use this data and say that the majority of disabled people in society claim PIP or DLA. If the sample size is big enough.

Disadvantages
•	Cannot use the results and say that something caused something else to happen. 
•	Background noise can influence results. Background noise is when unmeasured factors influence results. For example, if a question is about attitudes towards disabled people at a time when the press has launched a disability hate campaign, this will result in more negative results than normal.

Longitudinal data. This is when a specific group of people are measured over time, so we can track changes in their life. For this reason, it is also called life-course data. One example of longitudinal data is the Life Opportunities Survey. This surveyed a group of individuals in 2009 and every two years the same individuals are asked to fill in the survey again. Therefore the survey can measure things like how the barriers disabled people face change over time. 

Longitudinal data should be used when you want to track a complex situation over time to see what changes take place. 

Advantages
•	Can measure long-term changes 
•	Can look at the order at which events happen in an individuals’ life
•	Can investigate how age affects an individuals’ thought process. For example, does an individuals political allegiance change as they get older?
•	Can study an individual over their lifetime

Disadvantages
•	The results are complex, and needs a level of statistical knowledge 
•	Drop out. A number of people drop out of the survey, either by choosing not to do it anymore, by moving, or changing name etc.
•	It can become routine. Some people can remember what questions they were asked before and respond to the questions without thinking about their response. Meaning that their results are unreliable.
•	Only the results from first time the people are surveyed can be generalised/applied to the group of society you are trying to measure.

Evaluations. This is the only type of survey data where the effects of a policy/change can be studied, as can be seen in figure below. As people are measured both before and after the policy/change. However, it is not possible to find the absolute reason why something happened. 

Policy

Before

After

There are a number of types of evaluation research; systematic reviews; impact evaluation; routine monitoring (social indicators); cost-benefit analysis; and qualitative research. As these are very varied I will be looking at these one by one. 

Systematic reviews. This is a form of literature review – a summary of research that has been published in your subject area. Unlike normal literature reviews, systematic reviews looks at all the quality pieces of research that has been conducted in that area. Systematic reviews are also more focused than normal literature reviews - they focus on a specific research question and then identify and evaluate all the research related to that question.

This should be used when there is a lot of information available on a specific topic.

Advantages
•	It is a useful way of looking at all the different data that is produced
•	It allows you to look at a research question in more depth

Disadvantages
•	Can use uncertain research 
•	The differences between the types of data/research is not investigated
•	Time consuming
•	Often open to doubt – not always a clear answer to your research question

Impact evaluations. These enable us to examine the impact of a specific policy change. There are different types of impact evaluations, of which Randomised Control Trials (RCTs) are the most common. However, they are also the most controversial. In an RCT, people are randomly placed into two groups. One group are given the policy change while the other group (what we call a ‘control group’) is not. By comparing the differences between the two groups, we can see what impact the policy change has had.

However, it can be complex to divide a community into two groups, and there are a lot of other factors that can influence the results.  For example, if one friend has the policy change and another does not, they are likely to discuss it or share information. Therefore, the results of the evaluation will not be reliable.

Impact evaluations should be used when you want to identify the impact of particular policies on a population. 

Advantages
•	Can look at the impact a policy/change has had

Disadvantages
•	Cannot apply the result to another group of people
•	Sometimes can measure an impact that is not really there. The fact that an evaluation is taking place may generate excitement
•	Some impacts can not be measured for example, happiness or freedom

Routine monitoring. This is where a set of social indicators are monitored. For example, the Fulfilling Potential Indicators Outcome Framework is a set of social indictors (link below).  These are features of society which can be measured and which can change over time. This change (or sometime stability) is then assessed to see what it says about society. Indicators are normally measured using existing data, and can be used to see the value of policy(s) in addressing social issues. 
https://www.gov.uk/government/publications/fulfilling-potential-making-it-happen-for-disabled-people  

Routine monitoring should be used when you want to monitor changes over time, especially if you are influencing policy.

Advantages
•	Can measure aspects of society that are less visible 
•	Can be very focused

Disadvantages
•	Focuses on one thing – one statistic per indicator
•	Mainly uses existing data, so have no control over the way data is collected
•	Reliance on others to produce the data

Cost-benefit analysis. This is when you make a review of all the benefits you expect from a project or policy and compare it to all the costs involved. Cost-benefit analysis allows you to; decide whether to undertake a project; plan the objectives of the project; develop the measures of success; and estimate the resources required.

Cost-benefit analysis should be used when you need to examine the efficiency of a project.

Advantages
•	Is an easy way of estimating the worth of a project
•	Causes individuals to examine all aspects of a project
•	It can be moulded to reflect specific organisations

Disadvantages
•	Not all benefits/costs are put into the model
•	Difficulties in assigning a value/cost to social factors, for example, employee satisfaction 
•	It is an estimate

Qualitative research. As discussed previously qualitative research provides an in-depth study of a topic. In evaluations, it enables researchers to explain how a new initiative or service works, and what those involved (for example, disabled people receiving the service or staff delivering the service) think.  

Qualitative research should be used for evaluations when you want to find the opinion of individuals, ‘depth’ rather than the ‘bigger picture’.

Advantages
•	Gives voice to the marginalised 
•	Reveals core issues
•	In-depth analysis

Disadvantages
•	Results cannot be applied to another group of people or be repeated
•	It is based on a persons feelings or opinions 

Annex D – Types of analysis

Qualitative data analysis 
An example of qualitative research is the Equality and Human Rights Commission Research Report Opening up Work (Adams and Oldfield 2012). This research was conducted through group discussions (focus groups) and face-to-face interviews.  Through these they were able to split their findings into key themes which they were able to explore and support with a number of case studies. The research was designed to understand how work could be opened up to enable disabled people to participate, and how more employers can realise the potential of their disabled employees. Additionally they wanted to identity how workplaces could become more inclusive. This work fed into the Equality and Human Rights Commission’s Working Better programme.
http://www.equalityhumanrights.com/uploaded_files/research_report_77_opening_up_work.doc

Cross-sectional data analysis
An example of cross-sectional data is the Opinions and Lifestyle Survey. The Opinions and Lifestyle Survey conducts around 1,100 interviews a month, and is used to monitor a number of topics varying from well-being to tobacco usage. The DWP runs a set of questions (a module of questions) about disability on the Opinions and Lifestyle Survey. The link below is to a recent publication of results for this disability module. For this publication the data from the Opinions and Lifestyle Survey was analysed using descriptive statistics. Using descriptive statistics we were able to provide a picture of what views and opinions towards disability were for this time period. 
https://www.gov.uk/government/publications/disability-statistics-from-the-ons-opinions-and-lifestyle-survey-january-to-march-2013

Longitudinal data analysis
An example of longitudinal data is the Life Opportunities Survey. In 2009-10 nearly 10,000 households were interviewed. These results were published in December 2011. During 2010-11 the same people were interviewed again. These results will be published by the end of 2013. The data will be analysed by looking at the differences between the first set and second set of responses. For example, the report will look into individuals who have gained an impairment (people who did not have impairment in 2009-10 but do have one in 2010-11) and what effect this has had upon their lives. https://www.gov.uk/government/collections/life-opportunities-survey

Evaluations data analysis
An example of an evaluation is the Right to Control Pilot. Right to Control, was a pilot testing the legal right for disabled people to exercise greater choice and control over some of the support they receive in their daily lives. The evaluation involved two waves of qualitative interviews with customers, staff and member of the local co-production team involved in delivery and implementation. It also involved a survey of 1,700 customers in pilot and comparison areas to measure the impact that Right to Control had on a range of outcomes, including wellbeing and employment.  An economic study explored the cost effectiveness of Right to Control.  The synthesis report, which brings together findings from these three evaluation elements, is available on the ODI website.  
http://base-uk.org/sites/base-uk.org/files/news/13-07/rtc-synthesis-report.pdf

Common types of analysis

Quantitative techniques

Descriptive statistics. These are data tables and charts which look at the make up of your target group. For example, how many disabled people live in London? What is their age profile? What is their average income? This is the simplest statistics technique to use, but is very useful. 

In a large dataset it is a useful way of condensing information, for example, we can use it to tell us how many disabled people are in work in England, what is their average salary, what is their gender, their ethnicity, and what proportion of disabled people are in work.

Further guidance of how to conduct descriptive statistics can be found here:
http://www.princeton.edu/~otorres/Excel/excelstata.htm

Means testing. The most common types of means testing are ‘t-tests’ and ‘ANOVA’. 

T-tests should be used when you have two variables you want to compare, and ANOVA should be used when you have more that 2 variables. 

The t-test is designed to test whether two variables are related or not. It does this by comparing the means or proportions of the two variables. There are certain rules involved in this. A t-test should only be used to compare variables from different people or when comparing two different surveys.  For example, in a survey it can be used to compare men and women, or it can be used to compare the height of men in one country using one survey and the height of men in another country using a different survey.

Therefore in evaluations is only used to compare the treatment and control groups.  

For more guidance on how to conduct t-tests please see the link below:
http://www.gla.ac.uk/sums/users/narjis/stroke/indept1.html 

ANOVA is when you compare three or more groups of people. This can be when comparing variables from different people, or when a variable has three or more categories which you want to compare (for example comparing the age groupings 0-15; 16-64; and 65 and over). If a difference is found then you can use more complex statistical techniques, like regression, to try and discover what these differences are. 

More information on ANOVA can be found here:
http://explorable.com/one-way-anova	

Correlation. This looks at if two variables are linked or related in some way. Correlation also shows what type of relationship they have. It can tell us if the two variables have a positive relationship (for example calorie intake and weight – the more you eat the more likely you are to put on weight) or a negative relationship (for example temperature and number of clothes worn – the hotter it gets the less clothes people wear). The easiest way of seeing if two variables are correlated is by putting them in a scatter graph. If the points on the chart seem to be in a straight line then this signals that there is some correlation between the variables. To test how correlated the variables are, a statistical test needs to be carried out, which can be done in Microsoft Excel. The results of that test will be a number between -1 and 1; if the number is close to 1 then there is a positive correlation; if it is close to -1 then there is a negative correlation; and if it is near zero then there is no correlation.

The best example of correlation is height and weight. Running a correlation this would show that the two have a positive correlation relationship, as can be in the alongside chart.  So as an individuals height increases so does their weight.

It is important to be aware that correlation does not show whether one thing is causing another, it only shows whether there is a relationship. For example, a scatter plot of the number of pirates and global temperatures shows that there is a strong negative relationship between the two – if interpreted wrongly, someone could claim that the lack of pirates is causing global warming! Therefore, we have to be careful that we can back up a correlation with sort of explanation or theory.

Further information on how to conduct correlations can be found here:
http://www.socialresearchmethods.net/kb/statcorr.php 

Regression. This is one of the more technical statistical techniques. It looks at the relationship between a number of variables. What makes it different from correlation is that it can tell us how related the variables are. There are many types of regression. The one you use is dependent on the type of data being used. Here we will just be looking at linear regression, however, if you would like to look into more complex regression analysis you can use the links below. 
http://www.schatz.sju.edu/multivar/guide/Logistic.pdf 

Using linear regression you can see what variables have an influence on another variable. In order not to get confused it is important to label your variables correctly. One variable needs to be selected to be the dependent variable (y), this is normally your main variable as it is the variable that you test to see if any other variables are linked to it. The other variables selected are called explanatory variables (x). These are the variables which you are testing to see if they are related to, or could explain, your dependent (y) variable. 

The best way of explaining this is by looking at a fictional example. Say we wanted to look at the impact age has on bad health. We would run a regression where our dependent variable y=bad health and our explanatory variable x= age. We could use Microsoft Excel or any other statistical package to carry this out. The results would tell us if there is a relationship and by how much. 

As regression is in essence a line of best fit you are able to plot the results onto a graph, which are likely to look like the chart below. This shows that the two variables are positively related, meaning that the older you are the more likely your health is to deteriorate. On top of this it tells you that for every increase in age bad health increases by beta (ß)– the gradient of the slope. 

ß

For further guidance on how to conduct linear regression can be found here.
https://www.msu.edu/course/psy/403/StatDemos/Regression/Regression.htm
http://www.wikihow.com/Run-a-Multiple-Regression-in-Excel 

Segmentation. This is a way of dividing up a market/society to identify trends within it and create a profile of your target group. There are many different topics you can divide your market by, the main four are; geography; behaviour; demographics; and physical geography. It is a technique that is often used by service providers in order to tailor their marketing plans and services. The main way of doing segmentation is cluster analysis. This is when you categorise variables into subgroups. The most common way of clustering the variables is using a model called ‘k-means’. This looks each variables mean (average) and groups the variables with the closest means into subgroups. More information on cluster analysis can be found here:
http://www-users.cs.umn.edu/~kumar/dmbook/ch8.pdf

However, it is important to note that segmentation can be both qualitative and quantitative. 

More information on how to conduct segmentation analysis can be found here:
http://www.dobney.com/Research/segmentation.htm 

Qualitative analysis

Qualitative thematic analysis. This is the most common way of analysing qualitative data. It is a way of dividing data/information into themes. It is like a qualitative version of segmentation. The key in doing qualitative thematic analysis is to divide the data into the least number of themes, which reflect the data, as possible. This can be very complex and difficult, and involves the researcher absorbing themselves into the topic area.  These themes then become the way the data is categorised and coded in order to find meaningful patterns. An example of qualitative thematic analysis is the paper written by University College Dublin on the experience of unemployment in Ireland. The data was collected through 13 semi-structured focus groups carried out across Ireland in 2010. 
http://www.ucd.ie/geary/static/publications/workingpapers/gearywp201116.pdf

More detailed information on how to conduct qualitative thematic analysis can be found at these websites:
http://eprints.ncrm.ac.uk/468/1/1007_JTAHthematic_synthesis.pdf 
http://www.cin.ufpe.br/~ssj/Thematic%20networks%20an%20analytic%20tool%20for.pdf 

Evidence collection

Evidence synthesis. The main way of conducting an evidence synthesis is the qualitative approach, which is also called realist synthesis.  This is very similar to a systematic review (which is discussed in Annex C). However, realist synthesis goes beyond the collection of data/information on a topic. It looks beyond an article/publication to look at how decisions were made and draws conclusions on all parts of the article. The process involved in conducting a realist synthesis is; defining the scope of the review; searching for data and information and appraising it; extracting and merging the findings; and drawing conclusions and making recommendations.  

An example of an evidence synthesis is the Fulfilling Potential: Building a deeper understanding of disability in the UK today (link below); this drew together statistics and research to explore the nature of disability in the UK. 
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/320515/building-understanding-main-slide-deck.pdf 

This enabled us to combine all types of research to get a rounded view of disability. For example, for the section on access to leisure activities, this combined data from: Fulfilling Potential – Discussions so Far 2012; the Taking Part Survey 2010/11 (by Department of Culture Media and Sport); Active People Survey 5 (Sport England 2011); Life Opportunities Survey Wave 1 2009/11; and Life Opportunities Survey Qualitative Research with people with learning, memory or neuro-diversity impairment (Office for Disability Issues 2010). More information on how to conduct an evidence synthesis can be found here: 
http://www.ccsr.ac.uk/methods/publications/documents/RMPmethods2.pdf 

References

Adams L and Oldfield K (2012) ‘Opening up work: The views of disabled people and people with long-term health conditions’ Equality and Human Rights Commission Research Report
http://www.equalityhumanrights.com/uploaded_files/research/rr77_opening_up_work.pdf 

Glossary

Control group: in evaluation research a control group is the group of people that have not received any treatment or policy change etc. 

Cross-sectional: is a type of survey, where the people selected to take part are always selected randomly. 

Data set: is a collection of data taken from multiple people held in one place. For example, survey responses are all inputted into a data set.

DDA: Disability Discrimination Act.

Generalisable: able to be generalised.

Literature review: is a review of what has been published on a topic.

Longitudinal: is a type of survey, where the same group of people are asked to take part in a survey repeatedly over a period of time.

Mean: is the mathematical average. It is the sum of the values divided by the number of cases.

Median: is the middle value in a list of numbers.

Mode: is the most frequent value in a list of numbers.

Population: is the target group your research is investigating or related to.

Proportion: is the amount something is to part of the whole.  For example, the proportion of disabled people in the UK.

Representative: is an accurate representation of your target group. 

Qualitative: information that has been collected through conversations with people.

Quantitative: data that can be measured and analysed using numbers. 

Sample size: the number of people who responded to either the survey or a question. 

Sampling: the selection of individuals. In research it is the selection of individuals to take part in a survey.

Treatment group: in evaluation research a treatment group is the group of people who have received some form of treatment or policy change etc.

Variable: is a characteristic or number. In surveys it is the response given to a survey question or the survey question itself. 

Other disability related terminology:

AA: Attendance Allowance

CA: Carers Allowance

CAU: Carers Allowance Unit

DEA: Disability Employment Advisor

DLA: Disability Living Allowance

DRC: Disability Rights Commission

DWA: Disability Working Allowance

EDCP: Enhanced Disability Child Premium

EDP: Enhanced Disability Premium

ESA: Employment and Support Allowance

HRC: Higher Rate Care (a component of Disability Living Allowance)

HRCC: High Rate Care component

HRMC: Higher Rate Mobility Component (a component of Disability Living Allowance)

IB: Incapacity Benefit

IBLT: Incapacity Benefit Long Term Rate

IBST: Incapacity Benefit Short Term Higher Rate

IBY: Incapacity Benefit in Youth

CA: Invalid Care Allowance

ILF: Independent Living Fund

LA: Local Authority

MHAC: Mental Health Act Commission

MobA: Mobility Allowance

NDDP: New Deal for Disabled People

PIP: Personal Independence Payment

RtC: Right to Control

RTC: Residential Training Colleges

SDA: Severe Disablement Allowance

SSP: Statutory Sick Pay

Fulfilling Potential: the government’s new cross-cutting disability strategy.

UC: Universal Credit

Access to Work: advice to help overcome work related obstacles.

Work Programme: to help people find, prepare for and stay in work 

Work Choice: aimed at people who are experiencing complex barriers to work.

Index

DCLG: Department for Communities and Local Government

DfE: Department for Education

DfT: Department for Transport

DH: Department of Health

DLA: Disability Living Allowance

DWP: Department for Work and Pensions

HBAI: Households Below Average Income 

ONS: Office for National Statistics

PIP: Personal Independence Payment

RCT: Randomised Control Trial

SEN: Special Educational Needs

Web: www.gov.uk/government/publications/using-disability-data
Post: Office for Disability Issues, Department for Work and Pensions, Ground Floor, Caxton House, 6–12 Tothill Street, London SW1H 9NA
Email: fulfilling.potential@dwp.gsi.gov.uk
Telephone: 020 7340 4000
ISBN: 978-1-78425-063-8
Produced by the Department for Work and Pensions, January 2014
© Crown Copyright 2014