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Journal of Statistical Computation and Simulation Volume 77, 2007 - Issue 2
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Original Articles

An EM algorithm for regression analysis with incomplete covariate information

Zhiwei Zhang Division of Biostatistics, OSB/CDRH/FDA, 1350 Picard Drive, Rockville, MD, 20850, USA
&
Howard E. Rockette Department of Biostatistics, University of Pittsburgh, 130 DeSoto Street, Pittsburgh, PA, 15261, USACorrespondence[email protected]
Pages 163-173 | Received 01 Nov 2004, Published online: 24 Nov 2006

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Byungtae Seo. (2011) A gradient-based algorithm for semiparametric models with missing covariates. Journal of Statistical Computation and Simulation 81:4, pages 381-390.
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Articles from other publishers (9)

Osvaldo Espin‐Garcia, Radu V. Craiu & Shelley B. Bull. (2021) Two‐phase sample selection strategies for design and analysis in post‐genome‐wide association fine‐mapping studies. Statistics in Medicine 40:30, pages 6792-6817.
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Yang Zhao. (2020) Semiparametric model for regression analysis with nonmonotone missing data. Statistical Methods & Applications 30:2, pages 461-475.
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Menglu Che, Jerald F. Lawless & Peisong Han. (2020) Empirical and conditional likelihoods for two‐phase studies. Canadian Journal of Statistics 49:2, pages 344-361.
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J. F. Lawless. (2016) Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates. Lifetime Data Analysis 24:1, pages 28-44.
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Wei Liu, Bo Zhang, Hui Zhang & Zhiwei Zhang. (2014) Likelihood-based methods for evaluating principal surrogacy in augmented vaccine trials. Statistical Methods in Medical Research 26:2, pages 984-996.
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Yao-San Lin. (2016) Modeling with Insufficient Data to Increase Prediction Stability. Modeling with Insufficient Data to Increase Prediction Stability.
Frederico Z Poleto, Carlos Daniel Paulino, Julio M Singer & Geert Molenberghs. (2014) Semi-parametric Bayesian analysis of binary responses with a continuous covariate subject to non-random missingness. Statistical Modelling 15:1, pages 1-23.
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Yao-San Lin. (2010) Small sample regression: Modeling with insufficient data. Small sample regression: Modeling with insufficient data.
Yang Zhao, Jerald F. Lawless & Donald L. McLeish. (2009) Likelihood Methods for Regression Models with Expensive Variables Missing by Design. Biometrical Journal 51:1, pages 123-136.
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