We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unresolved by proposals involving modified p-value …
Monte-Carlo simulation was used to model the biasing of effect sizes in published studies. The findings from the simulation indicate that, when a predominant bias to publish studies with statistically significant results is coupled with inadequate …
We review and evaluate selection methods, a prominent class of techniques first proposed by Hedges (1984) that assess and adjust for publication bias in meta-analysis, via an extensive simulation study. Our simulation covers both restrictive settings …
This study compiles information from more than 250 meta-analyses conducted over the past 30 years to assess the magnitude of reported effect sizes in the organizational behavior (OB)/human resources (HR) literatures. Our analysis revealed an average …
Background The published clinical research literature may be distorted by the pursuit of statistically significant results. Purpose: We aimed to develop a test to explore biases stemming from the pursuit of nominal statistical significance. Methods …
We have created a curated scientific resource navigator called ARIADNE that will guide researchers in the field of life sciences, especially those at the beginning of their career, through the process of conducting a transparent and reproducible …
Sample correlations converge to the population value with increasing sample size, but the estimates are often inaccurate in small samples. In this report we use Monte-Carlo simulations to determine the critical sample size from which on the magnitude …
Several researchers recently outlined unacknowledged costs of open science practices, arguing these costs may outweigh benefits and stifle discovery of novel findings. We scrutinize these researchers’ (a) statistical concern that heightened …