Misstatements, misperceptions, and mistakes in controlling for covariates in observational research

2024/04/02 by X. D. Yu, Roger S. Zoh, David A Fluharty +8 · 1 voice
Medicine · Mathematics · Health Professions · #Nutritional Studies and Diet #Advanced Causal Inference Techniques #Food Security and Health in Diverse Populations

paper · doi:10.7554/elife.82268

openalex publication_date 2024/04/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

research. Additionally, we offer advice to help investigators, editors, reviewers, and readers make more informed decisions about conducting and interpreting research where the influence of covariates may be at issue. We primarily address misperceptions in the context of statistical management of the covariates through various forms of modeling, although we also emphasize design and model or variable selection. Other approaches to addressing the effects of covariates, including matching, have logical extensions from what we discuss here but are not dwelled upon heavily. The misperceptions, misstatements, or mistakes we discuss include accurate representation of covariates, effects of measurement error, overreliance on covariate categorization, underestimation of power loss when controlling for covariates, misinterpretation of significance in statistical models, and misconceptions about confounding variables, selecting on a collider, and p value interpretations in covariate-inclusive analyses. This condensed overview serves to correct common errors and improve research quality in general and in nutrition research specifically.

Citations

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Discussions

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