Efficient estimation of average treatment effects using the estimated propensity score

Keywords

Propensity score matching, Estimation, Statistics, Econometrics, Mathematics

References

• Approximation of FunctionsL. S. GODDARD — 1965
• Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary OutcomePeter Rosenbaum, Donald B. Rubin — 1983
• The asymptotic variance of semiparametric estimatorsWhitney K. Newey — 1994
• Convergence Rates for Series EstimatorsWhitney K. Newey — 1993
• Generalized Estimating EquationsJames W. Hardin, Joseph M. Hilbe — 2002
• Affinely Invariant Matching Methods with Ellipsoidal DistributionsDonald B. Rubin, Neal Thomas — 1992
• Toward a curse of dimensionality appropriate (CODA) asymptotic theory for semi-parametric models.James M. Robins, Ya’acov Ritov — 1997
• Asymptotic efficiency in estimation with conditional moment restrictionsGary Chamberlain — 1987
• Reducing Bias in Observational Studies Using Subclassification on the Propensity ScorePaul R. Rosenbaum, Donald B. Rubin — 1984
• INFERENCE AND MISSING DATADonald B. Rubin — 1975
• Matching using estimated propensity scores: relating theory to practice.Neal Thomas — 1996
• A Generalization of Sampling Without Replacement from a Finite UniverseDaniel G. Horvitz, Donovan J. Thompson — 1952
• Convergence rates and asymptotic normality for series estimatorsWhitney K. Newey — 1997
• Semiparametric Efficiency in Multivariate Regression Models with Missing DataJames M. Robins, Andrea Rotnitzky — 1995
• Inverse probability weighted M-estimators for sample selection, attrition, and stratificationJeffrey M. Wooldridge — 2002
• Imposing Moment Restrictions from Auxiliary Data by WeightingGuido W. Imbens, Judith K. Hellerstein — 1996
• Model-Based Direct AdjustmentPaul R. Rosenbaum — 1987
• Characterizing the effect of matching using linear propensity score methods with normal distributionsDonald B. Rubin, Neal Thomas — 1992
• Improved instrumental variables and generalized method of moments estimatorsHailong Qian, Peter Schmidt — 1999
• Nonparametric Maximum Likelihood Estimation by the Method of SievesStuart Geman, Chii-Ruey Hwang — 1982

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• Who Gets the Most Out of Cognitive-Behavioral Therapy for Anxiety Disorders?Sabine Fontana — 2013
• The impact of team-based primary care on health care services utilization and costs: Quebec's family medicine groups.Doris Breuer — 2017
• Population Average Gender EffectsTymon Słoczyński — 2013
• Evaluación de políticas públicas sobre poblaciones heterogéneas. ¿Pueden los órganos de control externo contribuir a su avance?José Manuel Cansino Muñoz-Repiso, Rocío Román Collado — 2007
• Testing for covariate balance in comparative studiesYevgeniya N. Kleyman — 2009
• Semiparametric Efficiency in GMM Models with Nonclassical Measurement ErrorXiaohong Chen, Alessandro Tarozzi — 2006
• The Causal Effect of School Reform: Evidence from California's Quality Education Investment ActPaul Burkander — 2013
• Causal inference and case-control studies with applications related to childhood diabetesEmma Persson — 2014
• Three Essays on Quantile RegressionLiang Wang — 2013
• The Value of Rapid Delivery in Online RetailingMarshall L. Fisher, Santiago Gallino, Joseph Xu — 2016
• Treatrew: A User-Written Command for Estimating Average Treatment Effects by Reweighting on the Propensity ScoreGiovanni Cerulli — 2014
• Essays in empirical corporate finance: CEO compensation, social interactions, and M&AFeng Jiang — 2012
• Sufficient covariates and linear propensity analysisHui Guo, A. P. Dawid — 2010
• When Relatives Return: Interviews with Family Members of Returning Prisoners in Houston, TexasTracey Shollenberger — 2009
• Efficient estimation in missing data and survey sampling problemsSixia Chen — 2012

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