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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Language: | fas |
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Tehran University of Medical Sciences
2017-06-01
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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. |
first_indexed | 2024-12-14T06:08:34Z |
format | Article |
id | doaj.art-f4cb0f95b61d4c88900f1a06e47da2a2 |
institution | Directory Open Access Journal |
issn | 1735-7489 2228-7507 |
language | fas |
last_indexed | 2024-12-14T06:08:34Z |
publishDate | 2017-06-01 |
publisher | Tehran University of Medical Sciences |
record_format | Article |
series | مجله اپیدمیولوژی ایران |
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 |