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


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

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

Abstract:   (1568 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.

Full-Text [PDF 1723 kb]   (354 Downloads)    
Type of Study: Review Article | Subject: General
Received: 2017/06/13 | Accepted: 2017/06/13 | Published: 2017/06/13

Add your comments about this article : Your username or email:
Write the security code in the box

© 2017 All Rights Reserved | Iranian Journal of Epidemiology

Designed & Developed by : Yektaweb