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The debate about false positives in psychological research has led to a demand for higher statistical power. To meet this demand, researchers need to collect data from larger samples—which is important to increase replicability, but can be costly in both time and money (i.e., remuneration of...
Publication bias and questionable research practices in primary research can lead to badly overestimated effects in meta-analysis. Methodologists have proposed a variety of statistical approaches to correct for such overestimation. However, it is not clear which methods work best for data...
Methodological developments and software implementations are progressing at an increasingly fast pace. The introduction and widespread acceptance of preprint archived reports and open-source software have made state-of-the-art statistical methods readily accessible to researchers. At the same...
Effect sizes are underappreciated and often misinterpreted—the most common mistakes being to describe them in ways that are uninformative (e.g., using arbitrary standards) or misleading (e.g., squaring effect-size rs). We propose that effect sizes can be usefully evaluated by comparing them with...
Data documentation in psychology lags behind not only many other disciplines, but also basic standards of usefulness. Psychological scientists often prefer to invest the time and effort that would be necessary to document existing data well in other duties, such as writing and collecting more...
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