Weighting regressions by propensity scores

Evaluation Review

Volumn 32, Issue 4, 2008, Pages 392-409

  Freedman, David A ^a   Berk, Richard A ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Causation; Experiments; Models; Observational studies; Propensity scores; Regression; Selection

Indexed keywords

ARTICLE; EPIDEMIOLOGY; METHODOLOGY; OBSERVATION; REGRESSION ANALYSIS; STATISTICAL MODEL;

CAUSALITY; MODELS, STATISTICAL; OBSERVATION; REGRESSION ANALYSIS; RESEARCH DESIGN; SELECTION BIAS;

EID: 46249111567     PISSN: 0193841X     EISSN: 15523926     Source Type: Journal    
DOI: 10.1177/0193841X08317586     Document Type: Article

References (30)

1. Arceneaux, K., A.S. Gerber, and D.P. Green. 2006. Comparing experimental and matching methods using a large-scale voter mobilization experiment. Political Analysis 14: 37-62.
2. Bang, H., and J.M. Robins. 2005. Doubly robust estimation in missing data and causal inference models. Biometrics 61: 962-72.
3. Bluthenthal, R.N., G. Ridgeway, T. Schell, R. Anderson, N.M. Flynn, and A.H. Kral. 2006. Examination of the association between syringe exchange program (SEP) dispensation policy and SEP client-level syringe coverage among injection drug users. Addiction 102: 638-46.
4. Crump, R.K., V. J. Hotz, G.W. Imbens, and O.A. Mitnik. 2007. Dealing with limited overlap in estimation of average treatment effects. Technical report, Department of Economics, University of California, Berkeley.
5. Doss, H., and J. Sethuraman. 1989. The price of bias reduction when there is no unbiased estimate. Annals of Statistics 17: 440-42.
6. Evans, S.N., and P.B. Stark. 2002. Inverse problems as statistics. Inverse Problems 18: R1-43.
7. Francesconi, M., and C. Nicoletti. 2006. Intergenerational mobility and sample selection in short panels. Journal of Applied Econometrics 21: 1265-93.
8. Freedman, D.A. 2005. Statistical models: Theory and practice. New York: Cambridge University Press.
9. - -. 2006. On the so-called ''Huber sandwich estimator'' and ''robust'' standard errors. The American Statistician 60: 299-302.
10. - -. 2008. Some general theory for weighted regressions. http://www.stat.berkeley.edu/ census/wtheory.pdf.
11. Glazerman, S., D.M. Levy, and D. Myers. 2003. Nonexperimental versus experimental estimates of earnings impacts. Annals of the American Academy of Political and Social Science 589: 63-93.
12. Gozalo, P.L., and S.C. Miller. 2007. Predictors of mortality: Hospice enrollment and evaluation of its causal effect on hospitalization of dying nursing home patients. Health Services Research 42: 587-610.
13. Heckman, J.J. 1978. Dummy endogenous variables in a simultaneous equation system. Econometrica 46: 931-59.
14. - -. 1979. Sample selection bias as a specification error. Econometrica 47: 153-61.
15. Hernn, M.A., B. Brumback, and J.M. Robins. 2001. Marginal structural models to estimate the joint causal effects of nonrandomized treatments. Journal of the American Statistical Association 96: 440-48.
16. Hirano, K., and G.W. Imbens. 2001. Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization. Health Services and Outcomes Research Methodology 2: 259-78.
17. Kang, J.D.Y., and J.L. Schafer. 2007. Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data. Statistical Science 22: 523-39.
18. Leslie, S., and P. Theibaud. 2007. Using propensity scores to adjust for treatment selection bias. SAS Global Forum 2007: Statistics and Data Analysis, paper 184- 2007, April 16-19, Orlando, FL.
19. Lunceford, J.K., and M. Davidian. 2004. Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study. Statistics in Medicine 23: 2937-60.
20. McNiel, D.E., and R.L. Binder. 2007. Effectiveness of mental health court in reducing recidivism and violence. American Journal of Psychiatry 164: 1395-1403.
21. Ridgeway, G., D. McCaffrey, and A. Morral. 2006. Toolkit for weighting and analysis of nonequivalent groups: A tutorial for the TWANG Package. Santa Monica, CA: RAND Corporation.
22. Robins, J.M., and A. Rotnitzky. 1992. Recovery of information and adjustment for dependent censoring using surrogate markers. In AIDS epidemiology-Methodological issues, ed. N. Jewell, K. Dietz, and V. Farewell, 297-331. Boston: Birkhuser.
23. - -. 1995. Semiparametric efficiency in multivariate regression models with missing data. Journal of the American Statistical Association 90: 122-29.
24. Robins, J.M., A. Rotnitzky, and L.P. Zhao. 1994. Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association 89: 846-66.
25. Robins, J.M., M. Sued, Q. Lei-Gomez, and A. Rotnitzky. 2007. Performance of double-robust estimators when ''inverse probability'' weights are highly variable. Statistical Science 22: 544-59.
26. Rotnitzky, A., J.M. Robins, and D.O. Scharfstein. 1998. Semiparametric regression for repeated outcomes with nonignorable nonresponse. Journal of the American Statistical Association 93: 1321-39.
27. Sampson, R.J., J.H. Laub, and C. Wimer. 2006. Does marriage reduce crime? A counterfactual approach to within-individual causal effects. Criminology 44: 465-508.
28. Schonlau, M. 2006. Charging decisions in death-eligible federal cases (1995-2005): Arbitrariness, capriciousness, and regional variation. In Race and the decision to seek the death penalty in federal cases, ed. S. P. Klein, R. A. Berk, and L. J. Hickman. Technical Report #TR-389-NIJ, RAND Corporation, Santa Monica, CA.
29. Tita, G., and G. Ridgeway. 2007. The impact of gang formation on local pattern of crime. Journal of Research on Crime and Delinquency 44: 208-37.
30. Wilde, E.T., and R. Hollister. 2007. How close is close enough? Evaluating propensity score matching using data from a class size reduction experiment. Journal of Policy Analysis and Management 26: 455-77.