Author: Witton, Julia, Cornesse, Carina
Abstract: Data quality is known to be compromised when respondents cognitively shortcut the survey response process. This satisficing behavior leads to inaccurate and unreliable responses
that are hard to compensate after data collection. Thus, detecting and understanding survey satisficing is crucial for developing and implementing effective preventive measures in
longitudinal data collection contexts. We use repeated latent class analyses across three
waves of a self-administered mixed-mode panel survey to identify patterns of satisficing.
Moreover, we identify correlates and predictors of future satisficing. Results indicate that
the same three classes (”Optimizers”, ”Indifferents”, and ”ExtreMists”) replicate over
time. The identified classes differ in their socio-demographic composition and results vary
across survey modes (paper versus web). Most importantly, the particular satisficing strategy in one wave is predictive of satisficing in the following wave on the individual level,
suggesting potential for targeted interventions across panel waves.
Year of Publication: 2025
Editor: OSF
Institution: German Institute of Economic Research (DIW Berlin, DE), GESIS - Leibniz-Institut für Sozialwissenschaften Mannheim (DE)
doi: 10.31219/osf.io/f4cgz_v1
More Information: Link (Date: 04.04.2025)

FGZ-Dataset:
German Social Cohesion Panel (SCP)