Data sharing upon request and statistical consistency errors in psychology: A replication of Wicherts, Bakker and...

Sharing research data allows the scientific community to verify and build upon published work. However, data sharing is not common practice yet. The reasons for not sharing data are myriad: Some are practical, others are more fear-related. One particular fear is that a reanalysis may expose errors. For this explanation, it would be interesting to know whether authors that do not share data genuinely made more errors than authors who do share data. (Wicherts, Bakker and Molenaar 2011) examined errors that can be discovered based on the published manuscript only, because it is impossible to reanalyze unavailable data. They found a higher prevalence of such errors in papers for which the data were not shared. However, (Nuijten et al. 2017) did not find support for this finding in three large studies. To shed more light on this relation, we conducted a replication of the study by (Wicherts et al. 2011). Our study consisted of two parts. In the first part, we reproduced the analyses from (Wicherts et al. 2011) to verify the results, and we carried out several alternative analytical approaches to evaluate the robustness of the results against other analytical decisions. In the second part, we used a unique and larger data set that originated from (Vanpaemel et al. 2015) on data sharing upon request for reanalysis, to replicate the findings in (Wicherts et al. 2011). We applied statcheck for the detection of consistency errors in all included papers and manually corrected false positives. Finally, we again assessed the robustness of the replication results against other analytical decisions. Everything taken together, we found no robust empirical evidence for the claim that not sharing research data for reanalysis is associated with consistency errors.