Predicting and Preventing Non-Response in Cohort Studies

Funders: ESRC.
Name: Ian Plewis

This project is funded by ESRC as part of their Survey Design and Measurement Initiative and directed by Ian Plewis with Lisa Calderwood (CLS) and Rebecca Taylor (NatCen) as co-investigators.

Longitudinal surveys must overcome a number of methodological challenges. Foremost among these challenges is the attrition problem: the fact that subjects are lost from the surveys every time the sample is remeasured. This sample loss can arise from a failure to locate sample members, or from a failure to contact them, or because contacted subjects choose not to cooperate with the survey. There are two unfortunate consequences of sample loss: the sample becomes progressively smaller; and, often more importantly, the sample becomes less and less representative of the population of research interest because the propensity for subjects to be lost varies in a systematic way. Hence, there is the potential for inferences about change to be biased. The research will address the attrition problem in two linked ways: by testing whether it is possible to reduce the level of non-cooperation in the field, and by examining the characteristics of the three types of non-responders with a view to improving our ability to predict attrition and hence, in the future, to introduce measures to prevent it.

We tackle the first problem by exploiting the strength of randomised experiments to test hypotheses about non- cooperation. There is some evidence that subjects decline to continue to participate in longitudinal surveys not because of a deep-seated antipathy to surveys but for situational or circumstantial reasons. We test two ways of increasing cooperation: by using a leaflet that addresses known concerns, and by increasing the numbers of refusals that are reissued by allocating them to a different, and usually a more experienced interviewer. By 'crossing' these two components, we can see whether they each have an effect independent of the other or whether it is the combination of the two parts of the intervention that is most effective.

Our approach to the second research question - whether it is possible to learn more about the kinds of subjects that are lost from the survey - is based on sophisticated statistical modelling, supplemented by the collection of data from the interviewers and from the respondents after fieldwork is over. One advantage that longitudinal surveys have is that we can use data collected at earlier occasions to predict how respondents might respond to the prospect of a further contact. Our analyses will help to set limits to the predictability of non-response and thus to the benefits of implementing procedures in the field prior to interview to prevent it.

Although it is not possible for one relatively small research project to solve all the problems created for longitudinal surveys by attrition, this project will provide us with increased insights about the reasons for non-response in all its forms and, in turn, this understanding will lead both to better quality longitudinal data and to more powerful ways of adjusting for non-response in analyses.