Registro:

Referencias:

• Robins, J.M., Rotnitzky, A., Zhao, L.P., Estimation of regression coefficients when some regressors are not always observed (1994) J Am Stat Assoc, 89 (427), pp. 846-866
• Robins, J.M., Rotnitzky, A., Zhao, L.P., Analysis of semiparametric regression models for repeated outcomes in the presence of missing data (1995) J Am Stat Assoc, 90 (429), pp. 106-121
• Little, R., An, H., Robust likelihood-based analysis of multivariate data with missing values (2004) Stat Sin, 14, pp. 949-968
• Kang, J.D., Schafer, J., Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data (2007) Stat Sci, 22, pp. 523-539
• Rosenbaum, P., Propensity score (1998) Encyclopedia of Biostatistics, 5, pp. 3551-3555. , Armitage P, Colton T, eds., New York, Wiley New York
• Hirano, K., Imbens, G.W., Ridder, G., Efficient estimation of average treatment effects using the estimated propensity score (2003) Econometrica, 71 (4), pp. 1161-1189
• Lunceford, J.K., Davidian, M., Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study (2004) Stat Med, 23 (19), pp. 2937-2960
• Crump, R.K., Hotz, V.J., Imbens, G.W., Mitnik, O.A., Dealing with limited overlap in estimation of average treatment effects (2009) Biometrika, 96 (1), pp. 187-199
• Little, R.J., Rubin, D.B., (1987) Statistical analysis with missing data john wiley and sons
• Cole, S.R., Hernan, M.A., Constructing inverse probability weights for marginal structural models (2008) Am J Epidemiol, 168 (6), pp. 656-664
• Ritz, C., Baty, F., Streibig, J.C., Gerhard, D., Dose-response analysis using R (2015) PLos one, 10 (12). , Dec 30;
• Tager, I.B., Weiss, A., Rosner, B., Speizer, F.E., Effect of parental cigarette smoking on the pulmonary function of children (1979) Am J Epidemiol, 110 (1), pp. 15-26
• Tager, I.B., Weiss, S.T., Muñoz, A., Rosner, B., Speizer, F.E., Longitudinal study of the effects of maternal smoking on pulmonary function in children (1983) N Engl J Med, 309 (12), pp. 699-703
• Rosner, B., (1999) Fundamentals of Biostatistics, , 5th ed, CA, Duxbury, Pacific Grove
• Kahn, M., An exhalent problem for teaching statistics (2005) J Stat Educ, 13 (2)
• Lee, B.K., Lessler, J., Stuart, E.A., Improving propensity score weighting using machine learning (2010) Stat Med, 29 (3), pp. 337-346
• Kang, J., Chan, W., Kim, M.O., Steiner, P.M., Practice of causal inference with the propensity of being zero or one: assessing the effect of arbitrary cutoffs of propensity scores (2016) Commun Stat Appl Methods, 23 (1), pp. 1-20
• Rubin, D.B., Inference and missing data (1976) Biometrika, 63 (3), pp. 581-592
• Rosenbaum, P.R., Rubin, D.B., The central role of the propensity score in observational studies for causal effects (1983) Biometrika, 70 (1), pp. 41-55
• Horvitz, D.G., Thompson, D.J., A generalization of sampling without replacement from a finite universe (1952) J Am Stat Assoc, 47 (260), pp. 663-685
• Robins, J.M., Rotnitzky, A., Recovery of information and adjustment for dependent censoring using surrogate markers (1992) Aids Epidemiology, pp. 297-331. , Jewell N, Dietz K, Farewell VT, eds., Birkhäuser, Boston, Springer
• McCullagh, P., Nelder, J., (1989) Generalized Linear CRC Monograph on Statistics and Applied Probability, , New York, Springer Verlag
• Valdora, M., Yohai, V.J., Robust estimators for generalized linear models (2014) J Stat Plan Infer, 146, pp. 31-48
• Van der Vaart, A.W., (1998) Asymptotic statistics, , Vol 3. Cambridge University Press;
• Neyman, J., Sur les applications de la theorie des probabilits˜ aux experiences agricoles (1923) Essai des principes Roczniki Nauk Rolniczych, 10, pp. 1-51
• Rubin, D.B., Estimating causal effects of treatments in randomized and nonrandomized studies (1974) J Educ Psychol, 66 (5), p. 688
• Cole, S.R., Frangakis, C.E., The consistency statement in causal inference: a definition or an assumption? (2009) Epidemiology, 20 (1), pp. 3-5
• Stefanski, L.A., Boos, D.D., The calculus of M-estimation (2002) Am Stat, 56 (1), pp. 29-38
• Yao, L., Sun, Z., Wang, Q., Estimation of average treatment effects based on parametric propensity score model (2010) J Stat Plan Inference, 140 (3), pp. 806-816
• Hahn, J., On the role of the propensity score in efficient semiparametric estimation of average treatment effects (1998) Econometrica, pp. 315-331
• Wasserman, L., (2013) All of Statistics: a Concise Course in Statistical Inference, , New York, Springer Science and Business Media
• Marazzi, A., Yohai, V.J., Adaptively truncated maximum likelihood regression with asymmetric errors (2004) J Stat Plan Inference, 122 (1), pp. 271-291
• Niu, X., Hoff, P., (2014) Covreg: a simultaneous regression model for the mean and covariance R package version
• Friedman, J., Hastie, T., Tibshirani, R., Regularization paths for generalized linear models via coordinate descent (2010) J Stat Softw, 33 (1), p. 1

Citas:

---------- APA ----------

---------- CHICAGO ----------

---------- MLA ----------

---------- VANCOUVER ----------