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来源类型Working Paper
规范类型报告
DOI10.3386/w14086
来源IDWorking Paper 14086
Use of Propensity Scores in Non-Linear Response Models: The Case for Health Care Expenditures
Anirban Basu; Daniel Polsky; Willard G. Manning
发表日期2008-06-19
出版年2008
语种英语
摘要Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the combination of both as in doubly-robust estimators. However, comparison of these alternative methods is sparse in the context of data generated via non-linear models where treatment effects are heterogeneous, such as is in the case of healthcare cost data. In this paper, we compare the performance of alternative regression and propensity score-based estimators in estimating average treatment effects on outcomes that are generated via non-linear models. Using simulations, we find that in moderate size samples (n= 5000), balancing on estimated propensity scores balances the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates, raising concern about its use in non-linear outcomes generating mechanisms. We also find that besides inverse-probability weighting (IPW) with propensity scores, no one estimator is consistent under all data generating mechanisms. The IPW estimator is itself prone to inconsistency due to misspecification of the model for estimating propensity scores. Even when it is consistent, the IPW estimator is usually extremely inefficient. Thus care should be taken before naively applying any one estimator to estimate ATE in these data. We develop a recommendation for an algorithm which may help applied researchers to arrive at the optimal estimator. We illustrate the application of this algorithm and also the performance of alternative methods in a cost dataset on breast cancer treatment.
主题Econometrics ; Estimation Methods ; Health, Education, and Welfare ; Health
URLhttps://www.nber.org/papers/w14086
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/571762
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Anirban Basu,Daniel Polsky,Willard G. Manning. Use of Propensity Scores in Non-Linear Response Models: The Case for Health Care Expenditures. 2008.
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