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Multivariable models in orthopaedic research: a methodological review of covariate selection and causal relationships

机译：矫形研究中的多变量模型：协变量选择和因果关系的方法综述

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Objectives: The aim of this study was to evaluate the methods used for including or excluding covariates in a multivariable model and to find out how common is the Table 2 Fallacy in studies recently published in high-quality orthopaedic journals. Methods: A systematic review was conducted in the MEDLINE database. We included all studies that presented the results of a multivariable model in a table and published in seven orthopaedic journals with the highest ranked impact factors in 2019. Results: Table 2 Fallacy was found in 67% (129/193) of the evaluated studies in which a multivariable model was used. Only 16% (31/193) of all studies had included the variables based on causal inference. Furthermore, only three of these studies used causal diagrams to illustrate the causal inference. Altogether, 35% (67/193) of the studies included variables based on statistical methods. Conclusions: Confounder selection and the interpretation of the results of the multivariable model showed notable challenges in orthopaedic studies recently published in the top orthopaedic journals. Based on the results of our review, it seems that more education in statistics and increased knowledge is required to decrease the occurrence of these statistical issues in orthopaedic research. (c) 2021 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
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