The effect of events between waves on panel attrition
Panel surveys suffer from attrition. Most panel studies use propensity models or weighting class approaches to correct for non-random dropout. These models draw on variables measured in a previous wave or from paradata of the study. While it is plausible that they affect contactability and cooperati...
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European Survey Research Association
2015-04-01
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doaj-bb0682bef0664fa4bc5b715e11258e532020-11-24T22:54:26ZengEuropean Survey Research AssociationSurvey Research Methods1864-33611864-33612015-04-0191314310.18148/srm/2015.v9i1.58495697The effect of events between waves on panel attritionMark Trappmann0Tobias GramlichAlexander MosthafInstitute for Employment Research (IAB) Otto-Friedrich-Universität BambergPanel surveys suffer from attrition. Most panel studies use propensity models or weighting class approaches to correct for non-random dropout. These models draw on variables measured in a previous wave or from paradata of the study. While it is plausible that they affect contactability and cooperativeness, panel studies usually cannot assess the impact of events between waves on attrition. The amount of change in the population could be seriously underestimated if such events had an effect on participation in subsequent waves. The panel study PASS is a novel dataset for labour market and poverty research. In PASS, survey data on (un)employment histories, income and education of participants are linked to corresponding data from respondents' administrative records. Thus, change can be observed for attritors as well as for continued participants. These data are used to show that change in household composition, employment status or receipt of benefits has an influence on contact and cooperation rates in the following wave. A large part of the effect is due to lower contactability of households who moved. Nevertheless, this effect can lead to biased estimates for the amount of change. After applying the survey’s longitudinal weights this bias is reduced, but not entirely eliminated.https://ojs.ub.uni-konstanz.de/srm/article/view/5849panel surveyattritionnonresponseweighting |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mark Trappmann Tobias Gramlich Alexander Mosthaf |
spellingShingle |
Mark Trappmann Tobias Gramlich Alexander Mosthaf The effect of events between waves on panel attrition Survey Research Methods panel survey attrition nonresponse weighting |
author_facet |
Mark Trappmann Tobias Gramlich Alexander Mosthaf |
author_sort |
Mark Trappmann |
title |
The effect of events between waves on panel attrition |
title_short |
The effect of events between waves on panel attrition |
title_full |
The effect of events between waves on panel attrition |
title_fullStr |
The effect of events between waves on panel attrition |
title_full_unstemmed |
The effect of events between waves on panel attrition |
title_sort |
effect of events between waves on panel attrition |
publisher |
European Survey Research Association |
series |
Survey Research Methods |
issn |
1864-3361 1864-3361 |
publishDate |
2015-04-01 |
description |
Panel surveys suffer from attrition. Most panel studies use propensity models or weighting class approaches to correct for non-random dropout. These models draw on variables measured in a previous wave or from paradata of the study. While it is plausible that they affect contactability and cooperativeness, panel studies usually cannot assess the impact of events between waves on attrition. The amount of change in the population could be seriously underestimated if such events had an effect on participation in subsequent waves. The panel study PASS is a novel dataset for labour market and poverty research. In PASS, survey data on (un)employment histories, income and education of participants are linked to corresponding data from respondents' administrative records. Thus, change can be observed for attritors as well as for continued participants. These data are used to show that change in household composition, employment status or receipt of benefits has an influence on contact and cooperation rates in the following wave. A large part of the effect is due to lower contactability of households who moved. Nevertheless, this effect can lead to biased estimates for the amount of change. After applying the survey’s longitudinal weights this bias is reduced, but not entirely eliminated. |
topic |
panel survey attrition nonresponse weighting |
url |
https://ojs.ub.uni-konstanz.de/srm/article/view/5849 |
work_keys_str_mv |
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1725659861413265408 |