Volume 13, Issue 1 (Vol 13, No 1, Spring 2017)                   irje 2017, 13(1): 75-81 | Back to browse issues page

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Shakiba M, Mansournia M, Soori H. The Bias of Standard Methods in Estimating Causal Effect. irje 2017; 13 (1) :75-81
URL: http://irje.tums.ac.ir/article-1-5693-en.html
1- استادیار اپیدمیولوژی، مرکز تحقیقات علوم اعصاب، دانشکده بهداشت، دانشگاه علوم پزشکی گیلان، رشت، ایران
2- استادیار اپیدمیولوژی، گروه اپیدمیولوژی و آمار حیاتی ، دانشکده بهداشت، دانشگاه علوم پزشکی تهران، تهران، ایران
3- استاد اپیدمیولوژی، گروه اپیدمیولوژی، مرکز تحقیقات ارتقاء ایمنی و پیشگیری از مصدومیت ها، دانشکده بهداشت، دانشگاه علوم پزشکی شهید بهشتی، تهران، ایران , hsoori@yahoo.com
Abstract:   (7092 Views)

Standard methods for estimating exposure effects in longitudinal studies will result in biased estimates of the exposure effect in the presence of time-dependent confounders affected by past exposure.

 In the present review article, we first described the assumptions required for estimating the causal effect in longitudinal studies and their structure regarding various types of exposure and confounders; then, we explained the bias of standard methods in estimating the causal effect.

Two types of bias, i.e. over-adjustment bias and selection bias, occur in estimating the effect of time-varying exposure in the presence of time-dependent confounders affected by previous exposure using standard regression analysis. Standard regression methods cannot sufficiently modify time-dependent confounders and estimate the total causal effect of the exposure.

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Type of Study: Review Article | Subject: General
Received: 2017/06/13 | Accepted: 2017/06/13 | Published: 2017/06/13

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