• No results found

Albert, J.H. and Chib, S. (1993). “Bayesian Analysis of Binary and Polychotomous Response Data.” J. Am. Statist. Assoc., 88, 669-679.

Andridge, R. and Little, R.J. (2009). “Extensions of Proxy Pattern-Mixture Analysis for Survey Nonresponse.” Proceedings of the Survey Research Methods Section, American Statistical Association, 2009, 2468-2482.

Andridge, R. and Little, R.J. (2010). “A Review of Hot Deck Imputation for Survey Nonresponse.” International Statistical Review, 78, 1, 40-64.

Andridge, R. and Little, R.J. (2011). “Proxy Pattern-Mixture Analysis for Survey Nonresponse.” Journal of Official Statistics, 27, 153-180.

Baker, S. and Laird, N. (1988). “Regression Analysis for Categorical Variables with Outcome Subject to Nonignorable Nonresponse.” J. Am. Statist. Assoc., 83, 62-69.

Bang, H. and Robins, J.M. (2005). “Doubly robust estimation in missing data and causal inference models.” Biometrics, 61, 962–972.

Binder, D.A. (1982). “Non-Parametric Bayesian Models for Samples from Finite Populations.” J. R. Statist. Soc., 44, 388-393.

Brewer, K.R. and Mellor, R.W. (1973). “The Effect of Sample Structure on Analytical Surveys.” Austal. J. Statist., 15, 145-152.

Cao, W., Tsiatis, A.A., and Davidian, M. (2009). “Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data.” Biometrika, 96, 723-734. Daniels, M.J. and Hogan, J.W. (2000). “Reparameterizing the Pattern Mixture Model for Sensitivity Analyses under Informative Dropout.” Biometrics, 56, 1241-1248.

DuMouchel, W.H. and Duncan, G.J. (1983). “Using Sample Survey Weights in Multiple Regression Analysis of Stratified Samples.” J. Am. Statist. Assoc., 78, 535-543.

152

Gelman, A. (2007). “Struggles with Survey Weighting and Regression Modelling.” Statist. Sci., 22, 153-164.

Heckman, J. (1976). “The Common Structure of Statistical Models of Truncation, Sample Selection, Limited Dependent Variables and a Simple Estimator for Such Models.” Ann. Econ. Social Meas., 5, 475-492.

Kang, D.Y.J. and Schafer, J.L. (2007). “Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data.” Statist. Sci., 22, 523–539.

Little, R.J. (1986). “Survey nonresponse adjustments for estimates of means.” Int. Statist. Rev., 54, 139-157.

Little, R.J. (1993). “Pattern-Mixture Models for Multivariate Incomplete Data.” J. Am. Statist. Assoc., 88, 125-134.

Little, R.J. (1994). “A Class of Pattern-Mixture Models for Normal Incomplete Data.” Biometrika, 81, 471-483.

Little, R.J. and Rubin, D.B. (2002). Statistical Analysis with Missing Data (Second Edition). New York: Wiley.

Little, R.J. and An, H. (2004). “Robust Likelihood-Based Analysis of Multivariate Data with Missing Values.” Statistica Sinica, 14, 949–968.

Little, R.J. and Vartivarian, S. (2005). “Does weighting for nonresponse increase the variance of survey means?” Statistics Canada, 31, 161-168.

Little, R.J. (2012). “Calibrated Bayes, an Alternative Inferential Paradigm for Official Statistics.” Journal of Official Statistics, 28, 1-27.

Nandram, B., and Choi, J.W. (2002). “A Bayesian Analysis of a Proportion Under Non-Ignorable Nonresponse.” Statistics in Medicine, 21, 1189-1212.

Nordheim, E. (1984). “Inference From Nonrandomly Missing Categorical Data: An Example From a Genetic Study on Turner’s Syndrome.” J. Am. Statist. Assoc., 79, 772-780.

Pfeffermann, D. and Sikov, A. (2011). “Imputation and Estimation under Nonignorable Nonresponse in Household Surveys with Missing Covariate Information.” Journal of Official Statistics, 27, 181-209.

Robins, J.M., Rotnitzky, A., and Zhao, L.P. (1994). “Estimation of regression coefficients when some regressors are not always observed.” J. Am. Statist. Assoc., 89, 846–866.

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.

153

Rosenbaum, P.R. and Rubin, D.B. (1984). “Reducing bias in observational studies using subclassification on the propensity score.” J. Am. Statist. Assoc., 79, 516-524.

Rotnitzky, A., Robins, J.M., and Scharfstein, D.O. (1998). “Semiparametric regression for repeated measures outcomes with non-ignorable non-response.” J. Am. Statist. Assoc., 93, 1321–1339.

Rubin, D.B. (1974). “Characterizing the Estimation of Parameters in Incomplete Data Problems.” J. Am. Statist. Assoc., 69, 467-474.

Rubin, D.B. (1976). “Inference and Missing Data.” Biometrika, 63, 581-592.

Sarndal, C.E. and Lundstrom, S. (2008). “Assessing Auxiliary Vectors for Control of Nonresponse Bias in the Calibration Estimator.” Journal of Official Statistics, 24, 167-191.

Sarndal, C.E. (2011). “The 2010 Morris Hansen Lecture Dealing with Survey Nonresponse in Data Collection, in Estimation.” Journal of Official Statistics, 27, 1-21.

Schouten, B. (2007). “A Selection Strategy for Weighting Variables Under a Not-Missing-at- Random Assumption.” Journal of Official Statistics, 23, 51-68.

Sullivan, D. and Andridge, R. (2015). “A Hotdeck Imputation Procedure for Multiply Imputing Nonignorable Missing Data: The Proxy Pattern-Mixture Hotdeck.” Computational Statistics & Data Analysis, 82, 173-185.

Tsiatis, A.A. and Davidian, M. (2007). “Comment on ‘Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data.’” Statist. Sci., 22, 569–573.

Tsiatis, A.A., Davidian, M., and Cao, W. (2011). “Improved Doubly Robust Estimation When Data Are Monotonely Coarsened, with Application to Longitudinal Studies with Dropout.” Biometrics, 67, 536-545.

West, B. and Little, R.J. (2013). “Non-Response Adjustment of Survey Estimates Based on Auxiliary Variables Subject to Error.” Appl. Statist., 62, 213-231.

Zhang, G. and Little, R.J. (2008). “Extensions of the penalized spline propensity prediction method of imputation.” Biometrics, 65, 911–918.

Zhang, G. and Little, R.J. (2011). “A comparative study of doubly robust estimators of the mean with missing data.” J. Stat. Comput. Simul., 81, 2039-2058.

Zheng, H. and Little, R.J. (2005). “Inference for the population total from probability- proportional-to-size samples based on predictions from a penalized spline nonparametric model.” Journal of Official Statistics, 21, 1-20.

Related documents