Replicability of Simulation Studies for the Investigation of Statistical Methods: The RepliSims Project
K. Luijken, A. Lohmann, U. Alter, J. Claramunt Gonzalez, F.J. Clouth,, J.L. Fossum, L. Hesen, A.H.J. Huizing, J. Ketelaar, A.K. Montoya, L. Nab,, R.C.C. Nijman, B.B.L. Penning de Vries, T.D. Tibbe, Y.A. Wang, R.H.H., Groenwold

TL;DR
This study assesses the reproducibility of influential statistical simulation studies, finding that detailed reporting and open resources significantly enhance replicability, which is often hindered by insufficient information.
Contribution
It provides empirical evidence on the factors affecting the replicability of simulation studies and emphasizes the importance of transparent reporting and open data for reproducibility.
Findings
Replicability varies greatly among studies.
Open code and detailed descriptions facilitate replication.
Lack of information impedes reproducibility.
Abstract
Results of simulation studies evaluating the performance of statistical methods are often considered actionable and thus can have a major impact on the way empirical research is implemented. However, so far there is limited evidence about the reproducibility and replicability of statistical simulation studies. Therefore, eight highly cited statistical simulation studies were selected, and their replicability was assessed by teams of replicators with formal training in quantitative methodology. The teams found relevant information in the original publications and used it to write simulation code with the aim of replicating the results. The primary outcome was the feasibility of replicability based on reported information in the original publications. Replicability varied greatly: Some original studies provided detailed information leading to almost perfect replication of results, whereas…
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Taxonomy
TopicsMental Health Research Topics · Meta-analysis and systematic reviews · Scientific Computing and Data Management
