The sample size necessary to obtain a desired level of statistical power depends in part on the population value of the effect size, which is, by definition, unknown. A common approach to sample-size planning uses the sample effect size from a prior …
There is no crisis of replication and generalizability in psychological science, only misunderstanding or forgetting the fundamental nature of psychological phenomena and resultant implications for empirical testing. Stability–variability is the …
This article uses distributional matching and posterior predictive checks to estimate the extent of false and inflated findings in empirical research on strategic management. Based on a sample of 300 papers in top outlets for research on strategic …
Across the social sciences, growing concerns about research transparency have led to calls for pre-analysis plans (PAPs) that specify in advance how researchers intend to analyze the data they are about to gather. PAPs promote transparency and …
In the light of continuing debate over the applications of significance testing in psychology journals and following the publication of J. Cohen's (1994) article, the Board of Scientific Affairs (BSA) of the American Psychological Association (APA) …
This paper discusses the need and importance of statistical power analysis in field-based empirical research in Production and Operations Management (POM) and related disciplines. The concept of statistical power analysis is explained in detail and …
Objective. —To describe the pattern over time in the level of statistical power and the reporting of sample size calculations in published randomized controlled trials (RCTs) with negative results. Design. —Our study was a descriptive survey. Power …
Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this …