The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams

Abstract Background Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is,...

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Bibliographic Details
Main Authors: Yuanyuan Yu, Hongkai Li, Xiaoru Sun, Ping Su, Tingting Wang, Yi Liu, Zhongshang Yuan, Yanxun Liu, Fuzhong Xue
Format: Article
Language:English
Published: BMC 2017-12-01
Series:BMC Medical Research Methodology
Subjects:
Confounding equivalence
Logistic regression model
Inverse probability weighting based marginal structural model
Simulation study
Causal diagrams
Online Access:http://link.springer.com/article/10.1186/s12874-017-0449-7

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http://link.springer.com/article/10.1186/s12874-017-0449-7

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