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## Pre-registrations: The project was pre-registered twice. The first is the pre-registration on December 3rd, 2018, for the Belgian, French-language offline sample. This version did not include an R script, only the descriptions of planned analyses. The second pre-registration was done on March 3rd, 2019, and does include an R script. ### Material Both registrations include the material used for the respective studies You can find the respective files in Files => Material_English_Online => Documents And Files => Material_French_offline => Documents or under the "Registrations" tab. ### Analysis Scripts Since pre-registering the analysis script for study 2, we modified them considerably (although the analyses themselves remain very largely the same). The main purpose of this was to make them work more reliably and easier to understand, as well as work around some problems we had integrating the results in the manuscript using the R package papaja. This means that most results are wrapped in additional functions to generate output that can be directly loaded into the manuscript markdown file, which can make the result more difficult to read in the console output. If you prefer the normal output, remove the print_apa() command from the respective lines. Please check different versions if you are interested in their evolution. You can find the pre-registered version under the "Registration" tab, and the up-to-date versions under Files => Material_English_Online => Command Files and Files => Material_French_Offline => Command Files ### Metadata The [codebooks](https://juliafrischling.github.io/JuliaEberlen.github.io/privacy_codebooks.html) were created in R with Ruben Arslan's [codebook package](https://rubenarslan.github.io/codebook/index.html) ### Manuscript We prepared the manuscript mainly using the R papaja package https://github.com/crsh/papaja and then edited the generated word document in the feedback and revision rounds between co-authors. We also transformed the Bayes factors manually to be uniformly informative of the alternative hypothesis (Bayes factor 10) instead of switching between Bayes factors 10 and 01. If you are interested in the original markdown file, please let me (Julia) know, but be aware that it does not reflect the end state of the manuscript, and is in no way "best practice" of how to use Papaja
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