Tags

Type your tag names separated by a space and hit enter

The performance of different propensity score methods for estimating marginal odds ratios.
Stat Med. 2007 Jul 20; 26(16):3078-94.SM

Abstract

The propensity score which is the probability of exposure to a specific treatment conditional on observed variables. Conditioning on the propensity score results in unbiased estimation of the expected difference in observed responses to two treatments. In the medical literature, propensity score methods are frequently used for estimating odds ratios. The performance of propensity score methods for estimating marginal odds ratios has not been studied. We performed a series of Monte Carlo simulations to assess the performance of propensity score matching, stratifying on the propensity score, and covariate adjustment using the propensity score to estimate marginal odds ratios. We assessed bias, precision, and mean-squared error (MSE) of the propensity score estimators, in addition to the proportion of bias eliminated due to conditioning on the propensity score. When the true marginal odds ratio was one, then matching on the propensity score and covariate adjustment using the propensity score resulted in unbiased estimation of the true treatment effect, whereas stratification on the propensity score resulted in minor bias in estimating the true marginal odds ratio. When the true marginal odds ratio ranged from 2 to 10, then matching on the propensity score resulted in the least bias, with a relative biases ranging from 2.3 to 13.3 per cent. Stratifying on the propensity score resulted in moderate bias, with relative biases ranging from 15.8 to 59.2 per cent. For both methods, relative bias was proportional to the true odds ratio. Finally, matching on the propensity score tended to result in estimators with the lowest MSE.

Authors+Show Affiliations

Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada. peter.austin@ices.on.ca

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

17187347

Citation

Austin, Peter C.. "The Performance of Different Propensity Score Methods for Estimating Marginal Odds Ratios." Statistics in Medicine, vol. 26, no. 16, 2007, pp. 3078-94.
Austin PC. The performance of different propensity score methods for estimating marginal odds ratios. Stat Med. 2007;26(16):3078-94.
Austin, P. C. (2007). The performance of different propensity score methods for estimating marginal odds ratios. Statistics in Medicine, 26(16), 3078-94.
Austin PC. The Performance of Different Propensity Score Methods for Estimating Marginal Odds Ratios. Stat Med. 2007 Jul 20;26(16):3078-94. PubMed PMID: 17187347.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - The performance of different propensity score methods for estimating marginal odds ratios. A1 - Austin,Peter C, PY - 2006/12/26/pubmed PY - 2007/8/28/medline PY - 2006/12/26/entrez SP - 3078 EP - 94 JF - Statistics in medicine JO - Stat Med VL - 26 IS - 16 N2 - The propensity score which is the probability of exposure to a specific treatment conditional on observed variables. Conditioning on the propensity score results in unbiased estimation of the expected difference in observed responses to two treatments. In the medical literature, propensity score methods are frequently used for estimating odds ratios. The performance of propensity score methods for estimating marginal odds ratios has not been studied. We performed a series of Monte Carlo simulations to assess the performance of propensity score matching, stratifying on the propensity score, and covariate adjustment using the propensity score to estimate marginal odds ratios. We assessed bias, precision, and mean-squared error (MSE) of the propensity score estimators, in addition to the proportion of bias eliminated due to conditioning on the propensity score. When the true marginal odds ratio was one, then matching on the propensity score and covariate adjustment using the propensity score resulted in unbiased estimation of the true treatment effect, whereas stratification on the propensity score resulted in minor bias in estimating the true marginal odds ratio. When the true marginal odds ratio ranged from 2 to 10, then matching on the propensity score resulted in the least bias, with a relative biases ranging from 2.3 to 13.3 per cent. Stratifying on the propensity score resulted in moderate bias, with relative biases ranging from 15.8 to 59.2 per cent. For both methods, relative bias was proportional to the true odds ratio. Finally, matching on the propensity score tended to result in estimators with the lowest MSE. SN - 0277-6715 UR - https://www.unboundmedicine.com/medline/citation/17187347/The_performance_of_different_propensity_score_methods_for_estimating_marginal_odds_ratios_ DB - PRIME DP - Unbound Medicine ER -
Try the Free App:
Prime PubMed app for iOS iPhone iPad
Prime PubMed app for Android
Prime PubMed is provided
free to individuals by:
Unbound Medicine.