Peter Lugtig, University of Essex/ Utrecht University
Latent class models can be used to study attrition (drop-out) patterns in panel surveys. The advantage of using a Latent Class Model over other models, is that there are fewer assumptions with regards to the pattern of attrition in the survey. People in a panel survey may drop out and never return (monotone attrition), but any other (non-monotone) attrition pattern is possible as well. Using a Latent Class model, respondents can be grouped into homogeneous classes that each follow a different attrition pattern.
The latent class variable can subsequently be used in several ways. Differences on substantive variables can be investigated when the latent class variable is used to predict one or more dependent variables for example. Another possibility of interest to survey methodologists, is the study of measurement errors within each attrition class. In this way, it is possible to estimate measurement errors for every class of people who drop out, and ultimately, to study whether there is any relation between attrition error and measurement error. For example, is it true that who drop out quickly report with more measurement error than respondents who participate in every wave of a panel survey?
This presentation outlines different statistical methods to investigate attrition patterns, determine the number of Latent Classes and develop Latent Class indicators for attrition. Data from the British Household Panel will be used to illustrate how the profiles of different Latent classes of people who drop out differ from eachother.