메뉴 건너뛰기




Volumn 29, Issue 6, 2014, Pages 1727-1748

Targeted smoothing parameter selection for estimating average causal effects

Author keywords

Causal inference; Double smoothing; Local linear regression

Indexed keywords


EID: 84912010652     PISSN: 09434062     EISSN: 16139658     Source Type: Journal    
DOI: 10.1007/s00180-014-0515-0     Document Type: Article
Times cited : (6)

References (25)
  • 1
    • 0001338126 scopus 로고
    • Asymptotic optimality of generalized cl, cross-validation, and generalized cross-validation in regression with heteroskedastic errors
    • Andrews DWK (1991) Asymptotic optimality of generalized cl, cross-validation, and generalized cross-validation in regression with heteroskedastic errors. J Econom 47:359–377
    • (1991) J Econom , vol.47 , pp. 359-377
    • Andrews, D.W.K.1
  • 2
    • 84950937870 scopus 로고
    • Nonparametric estimation of mean functionals with data missing at random
    • Cheng PE (1994) Nonparametric estimation of mean functionals with data missing at random. J Am Stat Assoc 89:81–87
    • (1994) J Am Stat Assoc , vol.89 , pp. 81-87
    • Cheng, P.E.1
  • 3
    • 84936916896 scopus 로고
    • Robust locally weighted regression and smoothing scatterplots
    • Cleveland WS (1979) Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc 74:829–836
    • (1979) J Am Stat Assoc , vol.74 , pp. 829-836
    • Cleveland, W.S.1
  • 4
    • 0002384709 scopus 로고
    • Conditional independence in statistical theory
    • Dawid AP (1979) Conditional independence in statistical theory. J R Stat Soc Ser B Stat Methodol 41:1–31
    • (1979) J R Stat Soc Ser B Stat Methodol , vol.41 , pp. 1-31
    • Dawid, A.P.1
  • 5
    • 84899913516 scopus 로고    scopus 로고
    • Sensitivity analysis of the unconfoundedness assumption with an application to an evaluation of college choice effects on earnings
    • de Luna X, Lundin M (2014) Sensitivity analysis of the unconfoundedness assumption with an application to an evaluation of college choice effects on earnings. J App Stat 41:1–18
    • (2014) J App Stat , vol.41 , pp. 1-18
    • de Luna, X.1    Lundin, M.2
  • 6
    • 82055199021 scopus 로고    scopus 로고
    • Covariate selection for the nonparametric estimation of an average treatment effect
    • de Luna X, Waernbaum I, Richardson TS (2011) Covariate selection for the nonparametric estimation of an average treatment effect. Biometrika 98:861–875
    • (2011) Biometrika , vol.98 , pp. 861-875
    • de Luna, X.1    Waernbaum, I.2    Richardson, T.S.3
  • 7
    • 84950423285 scopus 로고
    • Design-adaptive nonparametric regression
    • Fan J (1992) Design-adaptive nonparametric regression. J Am Stat Assoc 87:998–1004
    • (1992) J Am Stat Assoc , vol.87 , pp. 998-1004
    • Fan, J.1
  • 9
    • 21644482489 scopus 로고    scopus 로고
    • Matching estimators and optimal bandwidth choice
    • Frölich M (2005) Matching estimators and optimal bandwidth choice. Stat Comput 15:197–215
    • (2005) Stat Comput , vol.15 , pp. 197-215
    • Frölich, M.1
  • 10
    • 34249042306 scopus 로고    scopus 로고
    • Nonparametric IV estimation of local average treatment effects with covariates
    • Frölich M (2007) Nonparametric IV estimation of local average treatment effects with covariates. J Econom 139:35–75
    • (2007) J Econom , vol.139 , pp. 35-75
    • Frölich, M.1
  • 11
    • 84885022472 scopus 로고    scopus 로고
    • Bandwidth selection for backfitting estimation of semiparametric additive models: a simulation study
    • Häggström J (2013) Bandwidth selection for backfitting estimation of semiparametric additive models: a simulation study. Comput Stat Data Anal 62:136–148
    • (2013) Comput Stat Data Anal , vol.62 , pp. 136-148
    • Häggström, J.1
  • 12
    • 44849091245 scopus 로고    scopus 로고
    • The prognostic analogue of the propensity score
    • Hansen B (2008) The prognostic analogue of the propensity score. Biometrika 95:481–488
    • (2008) Biometrika , vol.95 , pp. 481-488
    • Hansen, B.1
  • 13
    • 0001079479 scopus 로고
    • Regression smoothing parameters that are not far from their optimum
    • Härdle W, Hall P, Marron J (1992) Regression smoothing parameters that are not far from their optimum. J Am Stat Assoc 87:227–233
    • (1992) J Am Stat Assoc , vol.87 , pp. 227-233
    • Härdle, W.1    Hall, P.2    Marron, J.3
  • 14
    • 1842429563 scopus 로고    scopus 로고
    • Nonparametric estimation of average treatment effects under exogeneity: a review
    • Imbens GW (2004) Nonparametric estimation of average treatment effects under exogeneity: a review. Rev Econ Stat 86:4–29
    • (2004) Rev Econ Stat , vol.86 , pp. 4-29
    • Imbens, G.W.1
  • 15
    • 84912056642 scopus 로고    scopus 로고
    • Imbens GW, Newey W, Ridder G (2005) Mean-squared-error calculations for average treatment effects. IEPR Working Papers 05.34, Institute of Economic Policy Research (IEPR)
    • Imbens GW, Newey W, Ridder G (2005) Mean-squared-error calculations for average treatment effects. IEPR Working Papers 05.34, Institute of Economic Policy Research (IEPR). http://dornsife.usc.edu/IEPR/Working%20Papers/IEPR_05.34_%5bImbens.Newey.Ridder%5d.pdf
  • 16
    • 64849112179 scopus 로고    scopus 로고
    • Recent developments in the econometrics of program evaluation
    • Imbens GW, Wooldridge JM (2009) Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
    • (2009) J. Econ. Lit. , vol.47 , pp. 5-86
    • Imbens, G.W.1    Wooldridge, J.M.2
  • 17
    • 84972526326 scopus 로고
    • On the application of probability theory to agricultural experiments. Essay on principles. Section 9. (1990), translated (with discussion)
    • Neyman J (1923) On the application of probability theory to agricultural experiments. Essay on principles. Section 9. (1990), translated (with discussion). Stat Sci 5:465–480
    • (1923) Stat Sci , vol.5 , pp. 465-480
    • Neyman, J.1
  • 18
    • 84947934780 scopus 로고
    • An effective bandwidth selector for local least squares regression
    • Opsomer JD, Sheather S, Wand M (1995) An effective bandwidth selector for local least squares regression. J Am Stat Assoc 90:1257–1270
    • (1995) J Am Stat Assoc , vol.90 , pp. 1257-1270
    • Opsomer, J.D.1    Sheather, S.2    Wand, M.3
  • 20
    • 77951622706 scopus 로고
    • The central role of the propensity score in observational studies for causal effects
    • Rosenbaum P, Rubin D (1983) The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
    • (1983) Biometrika , vol.70 , pp. 41-55
    • Rosenbaum, P.1    Rubin, D.2
  • 21
    • 58149417330 scopus 로고
    • Estimating causal effects of treatments in randomized and nonrandomized studies
    • Rubin DB (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. J Educ Psychol 66:688–701
    • (1974) J Educ Psychol , vol.66 , pp. 688-701
    • Rubin, D.B.1
  • 22
    • 21844518517 scopus 로고
    • Multivariate locally weighted least squares regression
    • Ruppert D, Wand M (1994) Multivariate locally weighted least squares regression. Ann Stat 22:1346–1370
    • (1994) Ann Stat , vol.22 , pp. 1346-1370
    • Ruppert, D.1    Wand, M.2
  • 23
    • 0000713437 scopus 로고
    • Kernel smoothing in partial linear models
    • Speckman P (1988) Kernel smoothing in partial linear models. J R Stat Soc Ser B Stat Methodol 50:413–436
    • (1988) J R Stat Soc Ser B Stat Methodol , vol.50 , pp. 413-436
    • Speckman, P.1
  • 24
    • 77949268346 scopus 로고    scopus 로고
    • Propensity score model specification for estimation of average treatment effects
    • Waernbaum I (2010) Propensity score model specification for estimation of average treatment effects. J Stat Plan Inference 140:1948–1956
    • (2010) J Stat Plan Inference , vol.140 , pp. 1948-1956
    • Waernbaum, I.1
  • 25
    • 0021657672 scopus 로고
    • Variance reduction techniques for digital simulation
    • Wilson JR (1984) Variance reduction techniques for digital simulation. Am J Math Manag Sci 4:277–312
    • (1984) Am J Math Manag Sci , vol.4 , pp. 277-312
    • Wilson, J.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.