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A Pseudo-Bayesian Shrinkage Approach to Regression with Missing Covariates

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  • Nanhua Zhang
  • Roderick J. Little

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  • Nanhua Zhang & Roderick J. Little, 2012. "A Pseudo-Bayesian Shrinkage Approach to Regression with Missing Covariates," Biometrics, The International Biometric Society, vol. 68(3), pages 933-942, September.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:3:p:933-942
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    References listed on IDEAS

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    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Joseph G. Ibrahim & Ming-Hui Chen & Stuart R. Lipsitz & Amy H. Herring, 2005. "Missing-Data Methods for Generalized Linear Models: A Comparative Review," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 332-346, March.
    3. J. G. Ibrahim & S. R. Lipsitz & M.‐H. Chen, 1999. "Missing covariates in generalized linear models when the missing data mechanism is non‐ignorable," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 173-190.
    4. Chen, Qingxia & Ibrahim, Joseph G. & Chen, Ming-Hui & Senchaudhuri, Pralay, 2008. "Theory and inference for regression models with missing responses and covariates," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1302-1331, July.
    5. Roderick J. Little & Nanhua Zhang, 2011. "Subsample ignorable likelihood for regression analysis with missing data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 60(4), pages 591-605, August.
    6. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
    7. Lan Huang & Ming-Hui Chen & Joseph G. Ibrahim, 2005. "Bayesian Analysis for Generalized Linear Models with Nonignorably Missing Covariates," Biometrics, The International Biometric Society, vol. 61(3), pages 767-780, September.
    8. Joseph G. Ibrahim & Ming-Hui Chen & Stuart R. Lipsitz, 1999. "Monte Carlo EM for Missing Covariates in Parametric Regression Models," Biometrics, The International Biometric Society, vol. 55(2), pages 591-596, June.
    9. Chen, Qingxia & Zeng, Donglin & Ibrahim, Joseph G., 2007. "Sieve Maximum Likelihood Estimation for Regression Models With Covariates Missing at Random," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1309-1317, December.
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