The True Role that Suppressor Effects Play in Condition-Based Regression Analysis: None. A Reply to Fiedler (2021)
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. Here, we provide readers with additional materials for the article Humberg, S., Dufner, M., Schönbrodt, F. D., Geukes, K., Hutteman, R., van Zalk, M. H. W., Denissen, J. J. A., Nestler, S., & Back, M. D. (2022). The true role that suppressor effects play in condition-based regression analysis: None. A reply to Fiedler (2021). Journal of Personality and Social Psychology, 123(4), 884–888. https://doi.org/10.1037/pspp0000428 The following files are provided: ComF_helpers.R is a background file that defines functions used in the other R code files (download the file, but you do not need to open it). ComF_ReproduceResults.R is the R code that reproduces all fake data, plots and results reported in the article. ComF_SOM.pdf is a Supplemental Online Material with the following contents: - 1. Mathematical Proof of the Suppressor Effect --- 1.1 Proof --- 1.2 Computational Examples --- 1.3 Simulated Examples (Including Code to Reproduce Fiedler’s Simulation Study) - 2. How to Inspect Example Data With Arbitrary PPZ-Correlation-Structures - 3. Suppressor Effects are Unconnected to SE Effect Patterns: Empirical Illustration - 4. Summary of Prior Discussions of Suppressor Effects in the Context of CRA ComF_SOM_Rcode.R is the R code that reproduces the contents of ComF_SOM.pdf. .
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.