The Bias of Standard Methods in Estimating Causal Effect

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 cau...

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Format: Article
Language:fas
Published: Tehran University of Medical Sciences 2017-06-01
Series:مجله اپیدمیولوژی ایران
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Online Access:http://irje.tums.ac.ir/article-1-5693-en.html
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collection DOAJ
description 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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spelling doaj.art-f4cb0f95b61d4c88900f1a06e47da2a22022-12-21T23:14:13ZfasTehran University of Medical Sciencesمجله اپیدمیولوژی ایران1735-74892228-75072017-06-011317581The Bias of Standard Methods in Estimating Causal Effect012 استادیار اپیدمیولوژی، مرکز تحقیقات علوم اعصاب، دانشکده بهداشت، دانشگاه علوم پزشکی گیلان، رشت، ایران استادیار اپیدمیولوژی، گروه اپیدمیولوژی و آمار حیاتی ، دانشکده بهداشت، دانشگاه علوم پزشکی تهران، تهران، ایران استاد اپیدمیولوژی، گروه اپیدمیولوژی، مرکز تحقیقات ارتقاء ایمنی و پیشگیری از مصدومیت ها، دانشکده بهداشت، دانشگاه علوم پزشکی شهید بهشتی، تهران، ایران 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.http://irje.tums.ac.ir/article-1-5693-en.htmlcausal effectstandard regression methodtime-dependent confounding
spellingShingle The Bias of Standard Methods in Estimating Causal Effect
مجله اپیدمیولوژی ایران
causal effect
standard regression method
time-dependent confounding
title The Bias of Standard Methods in Estimating Causal Effect
title_full The Bias of Standard Methods in Estimating Causal Effect
title_fullStr The Bias of Standard Methods in Estimating Causal Effect
title_full_unstemmed The Bias of Standard Methods in Estimating Causal Effect
title_short The Bias of Standard Methods in Estimating Causal Effect
title_sort bias of standard methods in estimating causal effect
topic causal effect
standard regression method
time-dependent confounding
url http://irje.tums.ac.ir/article-1-5693-en.html