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Replication Data for: The Misreporting Trade-off Between List Experiments and Direct Questions in Practice: Partition Validation Evidence from Two Countries

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication Data for: The Misreporting Trade-off Between List Experiments and Direct Questions in Practice: Partition Validation Evidence from Two Countries
 
Identifier https://doi.org/10.7910/DVN/W90Q7B
 
Creator Kuhn, Patrick
Vivyan, Nick
 
Publisher Harvard Dataverse
 
Description To reduce strategic misreporting on sensitive topics, survey researchers increasingly use list experiments rather than direct questions. However, the complexity of list experiments may increase non-strategic misreporting. We provide the first empirical assessment of this trade-off between strategic and non-strategic misreporting. We field list experiments on election turnout in two different countries, collecting measures of respondents' true turnout. We detail and apply a partition validation method which uses true scores to distinguish true and false positives and negatives for list experiments, thus allowing detection of non-strategic reporting errors. For both list experiments, partition validation reveals non-strategic misreporting that is: undetected by standard diagnostics or validation; greater than assumed in extant simulation studies; and severe enough that direct turnout questions subject to strategic misreporting exhibit lower overall reporting error. We discuss how our results can inform the choice between list experiment and direct question for other topics and survey contexts.
 
Subject Social Sciences
 
Contributor Code Ocean