How Changes in Common Practice Can Improve the Quality of Biomedical Science

Abstract

Assessing the impact of recommendations rectifying the reproducibility crisis (publishing both positive and \"negative\" results and increasing statistical power) on competing objectives, such as discovering causal relationships, avoiding publishing false positive results, and reducing resource consumption, we developed a new probabilistic model. Our model quantifies the impact of each single suggestion for an individual study and their relation and consequences for the entire research process. We can prove that higher-powered experiments can save resources in the overall research process without generating excess false positives. The better the quality of the pre-study information and its exploitation, the more likely this beneficial effect is to occur. Additionally, we quantify the adverse effects of neglecting good practices in the design and conduct of hypotheses-based research, and the responsibility to publish \"negative\" findings. Our contribution is a plea for adherence to or reinforcement of the good scientific practice and publication of \"negative\" findings.