'Statistical Irreproducibility' Does Not Improve with Larger Sample Size: How to Quantify and Address Disease Data Multimodality in Human and Animal Research.

ABSTRACT: Poor study reproducibility is a concern in translational research. As a solution, it is recommended to increase sample size (N), i.e., add more subjects to experiments. The goal of this study was to examine/visualize data multimodality (data with >1 data peak/mode) as cause of study irreproducibility. To emulate the repetition of studies and random sampling of study subjects, we first used various simulation methods of random number generation based on preclinical published disease outcome data from human gut microbiota-transplantation rodent studies (e.g., intestinal inflammation and univariate/continuous). We first used unimodal distributions (one-mode, Gaussian, and binomial) to generate random numbers. We showed that increasing N does not reproducibly identify statistical differences w

SUBMITTER: Basson AR 

PROVIDER: S-EPMC8005169 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature