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Volumn 68, Issue 3, 2012, Pages 680-686

Rejoinder: Bayesian Effect Estimation Accounting for Adjustment Uncertainty

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; UNCERTAINTY;

EID: 84866746931     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2011.01735.x     Document Type: Letter
Times cited : (20)

References (16)
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  • 2
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    • Functional restriction and efficiency in causal inference
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    • Causal inference with general treatment regimes: Generalizing the propensity score
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    • (2004) Journal of the American Statistical Association , vol.99 , pp. 854-866
    • Imai, K.1    van Dyk, D.A.2
  • 5
    • 1842429563 scopus 로고    scopus 로고
    • Nonparametric estimation of average treatment effects under exogeneity: A review
    • Imbens, G. W. (2004). Nonparametric estimation of average treatment effects under exogeneity: A review. Review of Economics and Statistics 86, 4-29.
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    • Imbens, G.W.1
  • 6
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    • The dangers of extreme counterfactuals
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  • 7
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    • Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study
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    • Lunceford, J.K.1    Davidian, M.2
  • 9
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    • The central role of the propensity score in observational studies for causal effects
    • Rosenbaum, P. R. and Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55.
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    • Rosenbaum, P.R.1    Rubin, D.B.2
  • 10
    • 84949193513 scopus 로고
    • Reducing bias in observational studies using subclassification on the propensity score
    • Rosenbaum, P. R. and Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association 79, 516-524.
    • (1984) Journal of the American Statistical Association , vol.79 , pp. 516-524
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  • 11
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  • 12
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    • Average causal effects from nonrandomized studies: A practical guide and simulated example
    • Schafer, J. and Kang, J. (2008). Average causal effects from nonrandomized studies: A practical guide and simulated example. Psychological Methods 13, 279-313.
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  • 13
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    • High-dimensional propensity score adjustment in studies of treatment effects using health care claims data
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    • Causal inference for continuous-time processes when covariates are observed only at discrete times
    • Zhang, M., Joffe, M. M., and Small, D. S. (2011). Causal inference for continuous-time processes when covariates are observed only at discrete times. Annals of Statistics 39, 131-173.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.