Mixing Modes in Longitudinal Surveys |
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| Coordinator 1 | Professor Mark Trappmann (Institute for Employment Research, University of Bamberg) |
| Coordinator 2 | Dr Mary Beth Ofstedal (Institute for Social Research, University of Michigan) |
The Covid-19 pandemic has forced many panel and cohort surveys to replace personal interviews by telephone or self-administered modes and thereby accelerated a trend of mixing modes in longitudinal surveys. While introducing new data collection modes helped prevent attrition or even the loss of entire survey waves during the pandemic, it also created new challenges for longitudinal surveys related to mode effects on survey measurement.
Many of the challenges presented by mode effects and the methodological tools for investigating and adjusting them differ between longitudinal and cross-sectional surveys. On the one hand, in longitudinal surveys the potential for harm is substantial. Even small mode-effects can dramatically affect estimates of change if the trait under investigation is relatively stable over time. On the other hand, longitudinal surveys allow exploiting within-subject variation and thus the application of more stringent methods to separate (self-)selection into mode from mode effects on measurement.
We invite submissions of research that investigate mode effects in a longitudinal setting. This may include mode experiments, analyses that separate selection effects from measurement effects, or approaches to separate mode effects from time trends and particularly from effects of the pandemic. We also invite contributions that address the impact of mode effects for longitudinal estimates and that offer solutions for communicating to users the importance of recognizing the potential for mode effects and how to deal with them in their research.