### Competition and moral behavior: A meta-analysis of 45 crowd-sourced experimental designs
*C. Huber, A. Dreber, J. Huber, M. Johannesson, M. Kirchler, U. Weitzel, M. Abellán, X. Adayeva, F. C. Ay, K. Barron, Z. Berry, W. Bönte, K. Brütt, M. Bulutay, P. Campos-Mercade, E. Cardella, M. A. Claassen, G. Cornelissen, I. G. J. Dawson, J. Delnoij, E. E. Demiral, E. Dimant, J. T. Doerflinger, M. Dold, C. Emery, L. Fiala, S. Fiedler, E. Freddi, T. Fries, A. Gasiorowska, U. Glogowsky, P. M. Gorny, J. D. Gretton, A. Grohmann, S. Hafenbrädl, M. Handgraaf, Y. Hanoch, E. Hart, M. Hennig, S. Hudja, M. Hütter, K. Hyndman, K. Ioannidis, O. Isler, S. Jeworrek, D. Jolles, M. Juanchich, R. P. KC, M. Khadjavi, T. Kugler, S. Li, B. Lucas, V. Mak, M. Mechtel, C. Merkle, E. A. Meyers, J. Mollerstrom, A. Nesterov, L. Neyse, P. Nieken, A.-M. Nussberger, H. Palumbo, K. Peters, A. Pirrone, X. Qin, R. M. Rahal, H. Rau, J. Rincke, P. Ronzani, Y. Roth, A. S. Saral, J. Schmitz, F. Schneider, A. Schram, S. Schudy, M. E. Schweitzer, C. Schwieren, I. Scopelliti, M. Sirota, J. Sonnemans, I. Soraperra, L. Spantig, I. Steimanis, J. Steinmetz, S. Suetens, A. Theodoropoulou, D. Urbig, T. Vorlaufer, J. Waibel, D. Woods, O. Yakobi, O. Yilmaz, T. Zaleskiewicz, S. Zeisberger, F. Holzmeister°*
° *corresponding author: felix.holzmeister@uibk.ac.at*
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#### Short-cut instructions
The reproduction package is prepared to allow a "push-button reproduction" of the results. No adjustments are needed. Simply open the file `scripts/__master.do` from within the folder (i.e., start Stata (v16) by opening the script file) and execute the file. That's it. All results will be logged in the console and exported to the sub-directories `logs`, `figures`, and `tables` in the folder `output`.
#### Comprehensive instructions
The analyses were prepared in *Stata MP 16.1* (on a workstation with a Windows 10 Enterprise (x64) operating system). On a Dell notebook with an Intel(R) Core(TM) i7-10610U CPU @1.80GHz (octa-core) with 32GB RAM, the script file `__master.do`, which executes all scripts sequentially, takes 216.4 seconds to complete (including the installation of user-written packages if not yet installed; if the packages are already installed, the computation time reduces to 201.6 seconds).
*All paths in the scripts are relative*, i.e., no adjustments are needed and no working directory needs to be defined. The only requirement is that the folder structure remains unchanged and the script files are opened directly from within the `scripts` folder such that the working directory is automatically set to the folder in which the respective file is located. Apart from Stata's standard functions and programs, the scripts use a few user-written programs (.ado-files). Required user-written programs are installed on-the-fly (if not yet installed), i.e., no manual installations are needed.
The reproduction package involves three directories: `data`, `scripts`, and `output`.
- The folder **`data`** contains three sub-directories: `raw`, `proc`, and `teams`. The folder `raw` includes the raw data on Prolific participants and research teams peer assessmeents in .csv-format. The `teams` folder comprises subdirectories for all reserach teams, containing the team's raw data, a codebook (if provided), and the analysis script generating the results for analytic approaches A, B, and C as well as the robustness analysis. The processed data (genderated by `scripts/0_data_processing.do` and `1_run_team_analyses.do`) are stored in folder `proc` (in .dta-format). The processed data files involve comprehensive variable labels, i.e., all variables are labeled in a self-explanatory way.
- The folder **`scripts`** contains the script files to process the data (`0_data_processing.do`), to generate the individual results for each of the 45 experimental designs (`1_run_team_analyses.do`), to conduct all pre-registered analyses reported in the paper and the supplementary materials (`2_meta_analysis.do`), and all not-preregistered analyses added to the paper during the review process (`3_added_analyses.do`). The files are numbered and must be executed in the given order (as temporarily stored data files are deleted to keep the repository well-organized). In addition, the folder involves a "master" file (`__master.do`), executing all scripts sequentially. Each script file provides a short description of the file contents in the header, including a list of input and output files. The `scripts` directory further contains two sub-folders: `figures` and `routines`. The folder `figures` includes the .do-files to generate figures 1 through 4 and S1 through S2 (which are called from within the scripts `0_data_processing.do`, `2_meta_analysis.do`, `3_added_analyses.do`. The `routines` folder contains a .do-file that defines custom programs called from within the analyses scripts. All of these custom programs rely on standard Stata commands but customize the console logs to enhance the organization and readability of the results/outputs.
- The **`output`** directory involves three sub-folders: `logs`, `figures`, and `tables`. The scripts `1_run_team_analyses.do`, `2_meta_analysis.do`, and `3_added_analyses.do` generate custom-formatted log-files (in .txt-format), equivalent to the logs reported in Stata's console when executing the scripts. The log files in `logs/meta_analysis` comprise all results reported in the main text and the supplementary materials. The scripts `0_data_processing.do`, `2_meta_analysis.do`, `3_added_analyses.do` also calls the scripts in `scripts/figures` and exports figures 1 trough 4 in the main text of the paper in high resolution (.png and .tif-format) and in vector format (.eps-format). `2_meta_analysis.do` and `3_added_analyses.do` also generate the summary tables S1 through S4 and well as S5 and S7 (as reported in the SI) in .xlsx-format. Tables S6 and S8 in the SI are based on the corresponding log-outputs in `logs`.
