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Replication Data for: Who's Cheating on Your Survey? A Detection Approach with Digital Trace Data

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

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Title Replication Data for: Who's Cheating on Your Survey? A Detection Approach with Digital Trace Data
 
Identifier https://doi.org/10.7910/DVN/WGWUK2
 
Creator Munzert, Simon
Ramirez-Ruiz, Sebastian
Barberá, Pablo
Guess, Andrew M.
Yang, JungHwan
 
Publisher Harvard Dataverse
 
Description In this note, we provide direct evidence of cheating in online assessments of political knowledge. We combine survey responses with web tracking data of a German and a U.S. online panel to assess whether people turn to external sources for answers. We observe item-level prevalence rates of cheating that range from 0 to 12\% depending on question type and difficulty, and find that 23\% of respondents engage in cheating at least once across waves. In the U.S. panel, which employed a commitment pledge, we observe cheating behavior among less than 1\% of respondents. We find robust respondent- and item-level characteristics associated with cheating. However, item-level instances of cheating are rare events; as such, they are difficult to predict and correct for without tracking data. Even so, our analyses comparing naive and cheating-corrected measures of political knowledge provide evidence that cheating does not substantially distort inferences.
 
Subject Social Sciences
 
Contributor Ramirez-Ruiz, Sebastian