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. 2023 Aug;58(4):3116-3131.
doi: 10.1111/ejn.16084. Epub 2023 Jul 13.

Misuse of multinomial logistic regression in stroke related health research: A systematic review of methodology

Nicholas Fitzhugh  1   2 , Line Ryberg Rasmussen  1 , Amalie Helme Simoni  1 , Jan Brink Valentin  1
Affiliations

Misuse of multinomial logistic regression in stroke related health research: A systematic review of methodology

Nicholas Fitzhugh et al. Eur J Neurosci. 2023 Aug.

Abstract

Multinomial logistic regression (MLR) is often used to model the association between a nominal outcome variable and one or more covariates. The results of MLR are interpreted as relative risk ratios (RRR) and warrant a more coherent interpretation than ordinary logistic regression. Some authors compare the results of MLR to ordinal logistic regression (OLR), irrespective of the fact that these estimate different quantities. We aim to investigate the time trends in the use and misuse of MLR in studies including stroke patients, specifically the extent to which (1) the results are denoted as anything other than RRR, (2) comparisons are made of results with results of OLR and (3) results have been interpreted coherently. Secondarily, we examine the use of model validation techniques in studies with predictive aims. We searched EMBASE and PubMed for articles using MLR on populations of stroke patients. Identified studies were screened, and information pertaining to our aims was extracted. A total of 285 articles were identified through a systematic literature search, and 68 of these were included in the review. Of these, 60 articles (88%) did not denote exponentiated coefficients of MLR as relative risk ratios but rather some other measure. Additionally, 63 articles (93%) interpreted the results of MLR in a non-coherent manner. Two articles attempted to compare MLR results with those of OLR. Nine studies attempted to use MLR for predictive means, and three used relevant validation techniques. From these findings, it is clear that the interpretation of MLR is often suboptimal.

Keywords: interpretation; modelling; odds ratio; relative risk ratio; risk ratio.

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