The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients
2013/01/30 by D. Westreich, Daniel Westreich, Sander Greenland +1 · 5 voices · 76 citations
Economics, Econometrics and Finance · Mathematics · #Advanced Causal Inference Techniques #Health Systems, Economic Evaluations, Quality of Life #Statistical Methods in Clinical Trials
paper · pdf · doi:10.1093/aje/kws412
openalex publication_date 2013/01/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
Abstract
It is common to present multiple adjusted effect estimates from a single model in a single table. For example, a table might show odds ratios for one or more exposures and also for several confounders from a single logistic regression. This can lead to mistaken interpretations of these estimates. We use causal diagrams to display the sources of the problems. Presentation of exposure and confounder effect estimates from a single model may lead to several interpretative difficulties, inviting confusion of direct-effect estimates with total-effect estimates for covariates in the model. These effect estimates may also be confounded even though the effect estimate for the main exposure is not confounded. Interpretation of these effect estimates is further complicated by heterogeneity (variation, modification) of the exposure effect measure across covariate levels. We offer suggestions to limit potential misunderstandings when multiple effect estimates are presented, including precise distinction between total and direct effect measures from a single model, and use of multiple models tailored to yield total-effect estimates for covariates.
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Discussions
- writing another review where I point to the Table 2 Fallacy (doi.org/10.1093/aje/... and doi.org/10.1017/psrm...) and say stop interpreting every single coefficient [bsky, 103 points, 6 comments]
- Westreich, D., & Greenland, S. (2013). The table 2 fallacy: Presenting and interpreting confounder and modifier coefficients. American Journal of Epidemiology, 177(4), 292–298. doi.org/10.1093/aje/... [bsky, 6 points, 1 comments]
- The paper mentioned in the video: doi.org/10.1093/aje/... [bsky, 6 points, 0 comments]
- #statstab #433 The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients
Thoughts: Adding predictors to your model results in marked changes in inference. Be mindful!
#ta [bsky, 5 points, 0 comments]
- This is basically the Table 2 fallacy on steroids (doi.org/10.1093/aje/...) [bsky, 2 points, 1 comments]
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