Propensity score methods to adjust for confounding in assessing treatment effects: bias and precision

Wang, Zhiqiang (2009) Propensity score methods to adjust for confounding in assessing treatment effects: bias and precision. The Internet Journal of Epidemiology, 7 2: x-x.

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Author Wang, Zhiqiang
Title Propensity score methods to adjust for confounding in assessing treatment effects: bias and precision
Formatted title
Propensity score methods to adjust for confounding in assessing treatment effects: bias and precision
Journal name The Internet Journal of Epidemiology
ISSN 1540-2614
Publication date 2009
Year available 2009
Sub-type Article (original research)
Open Access Status File (Publisher version)
Volume 7
Issue 2
Start page x
End page x
Total pages 16
Editor Florent Richy
Place of publication United States
Publisher Internet Scientific Publications, Llc.
Collection year 2010
Language eng
Subject C1
9204 Public Health (excl. Specific Population Health)
1117 Public Health and Health Services
Abstract There is an increasing interest in the use of propensity score (PS) methods for confounding control, with generally three ways of estimating adjusted treatment effects in pharmacoepidemiological studies: 1) stratification on PS, 2) matching on PS and 3) using PS as a covariate. To assess bias and precision of different methods, we conducted simulations in three scenarios: 1) treatment had no effect but the crude estimate showed a protective effect; 2) treatment was protective and the crude estimate was more extreme; and 3) treatment increased the risk but the crude estimate showed protective. Adjusting for confounders in all methods shifted the effect estimates toward the true values. Adjusted odds ratios using the PS stratification and the method using PS as a covariate were biased due to either residual confounding or over-adjustment. Matching on PS produced less biased average estimates than other methods but the precision of effect estimates was lower. --------------------------------------------------------------------------------
Formatted abstract
There is an increasing interest in the use of propensity score (PS) methods for confounding control, with generally three ways of estimating adjusted treatment effects in pharmacoepidemiological studies: 1) stratification on PS, 2) matching on PS and 3) using PS as a covariate. To assess bias and precision of different methods, we conducted simulations in three scenarios: 1) treatment had no effect but the crude estimate showed a protective effect; 2) treatment was protective and the crude estimate was more extreme; and 3) treatment increased the risk but the crude estimate showed protective. Adjusting for confounders in all methods shifted the effect estimates toward the true values. Adjusted odds ratios using the PS stratification and the method using PS as a covariate were biased due to either residual confounding or over-adjustment. Matching on PS produced less biased average estimates than other methods but the precision of effect estimates was lower.


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Keyword Propensity score method
confounding
logistic regression
simulation
Q-Index Code C1
Q-Index Status Confirmed Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2010 Higher Education Research Data Collection
School of Medicine Publications
 
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Created: Tue, 20 Apr 2010, 17:28:59 EST by Amanda Jones on behalf of Medicine - Royal Brisbane and Women's Hospital