Missing-Data Methods for Generalized Linear Models: A Comparative Review
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of the American Statistical Association.
Volume (Year): 100 (2005)
Issue (Month): (March)
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- Gretchen Carrigan & Adrian G. Barnett & Annette J. Dobson & Gita Mishra, . "Compensating for Missing Data from Longitudinal Studies Using WinBUGS," Journal of Statistical Software, American Statistical Association, vol. 19(i07).
- Yang, Ying & Kang, Jian, 2010. "Joint analysis of mixed Poisson and continuous longitudinal data with nonignorable missing values," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 193-207, January.
- Chen, Xue-Dong & Fu, Ying-Zi, 2011. "Model selection for zero-inflated regression with missing covariates," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 765-773, January.
- repec:ese:iserwp:2008-20 is not listed on IDEAS
- 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.
- Liang, Hua, 2008. "Generalized partially linear models with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 880-895, May.
- Francesco Lagona & Zhen Zhang, 2008. "A missing composite covariate in survival analysis: a case study of the Chinese Longitudinal Health and Longevity Survey," MPIDR Working Papers WP-2008-022, Max Planck Institute for Demographic Research, Rostock, Germany.
- Han, Peisong, 2012. "A note on improving the efficiency of inverse probability weighted estimator using the augmentation term," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2221-2228.
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