Questionable Research Practices and Cumulative Science: The Consequences of Selective Reporting on Effect Size Bias and Heterogeneity

Despite increased attention to open science and transparency, questionable research practices (QRPs) remain common, and studies published using QRPs will remain a part of the published record for some time. A particularly common type of QRP involves multiple testing, and in some forms of this, researchers report only a selection of the tests conducted. Methodological investigations of multiple testing and QRPs have often focused on implications for a single study, as well as how these practices can increase the likelihood of false positive results. However, it is illuminating to consider the role of these QRPs from a broader, literature-wide perspective, focusing on consequences that affect the interpretability of results across the literature. In this article, we use a Monte Carlo simulation study to explore the consequences of two QRPs involving multiple testing, cherry picking and question trolling, on effect size bias and heterogeneity among effect sizes. Importantly, we explicitly consider the role of real-world conditions, including sample size, effect size, and publication bias, that amend the influence of these QRPs. Results demonstrated that QRPs can substantially affect both bias and heterogeneity, although there were many nuances, particularly relating to the influence of publication bias, among other factors. The present study adds a new perspective to how QRPs may influence researchers’ ability to evaluate a literature accurately and cumulatively, and points toward yet another reason to continue to advocate for initiatives that reduce QRPs.