Background: Classic nonparametric tests (cNPTs), like Kruskal-Wallis or Mann-Whitney U, are sometimes used to detect differences in central tendency ( i.e., means or medians). However, when the tests' assumptions are violated, such as in the presence of unequal variance and other forms of heteroscedasticity, they are no longer valid for testing differences in central tendency. Yet, sometimes researchers erroneously use cNPTs to account for heteroscedasticity.
Objective: To document the appropriateness of cNPT use in obesity literature, characterize studies that use cNPTs, and evaluate the citation and public sharing patterns of these articles.
Methods: We reviewed obesity studies published in 2017 to determine whether the authors used cNPTs: (1) to correct for heteroscedasticity (invalid); (2) when heteroscedasticity was clearly not present (correct); or (3) when it was unclear whether heteroscedasticity was present (unclear). Open science R packages were used to transparently search literature and extract data on how often papers with errors have been cited in academic literature, read in Mendeley, and disseminated in the media.
Results: We identified nine studies that used a cNPT in the presence of heteroscedasticity (some because of the mistaken rationale that the test corrected for heteroscedasticity), 25 articles that did not explicitly state whether heteroscedasticity was present when a cNPT was used, and only four articles that appropriately reported that heteroscedasticity was not present when a cNPT was used. Errors were found in observational and interventional studies, in human and rodent studies, and only when studies were unregistered. Studies with errors have been cited 113 times, read in Mendeley 123 times, and disseminated in the media 41 times, by the public, scientists, science communicators, and doctors.
Conclusions: Examples of inappropriate use of cNPTs exist in the obesity literature, and those articles perpetuate the errors via various audiences and dissemination platforms.
Keywords: Nonparametric tests; heteroscedasticity; nutrition; obesity; open science; research rigor; statistical methods.
Copyright: © 2021 Kroeger CM et al.