A Semi-Parametric Shared Parameter Model to Handle Nonmonotone Nonignorable Missingness
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References listed on IDEAS
- Caroline Beunckens & Geert Molenberghs & Geert Verbeke & Craig Mallinckrodt, 2008. "A Latent-Class Mixture Model for Incomplete Longitudinal Gaussian Data," Biometrics, The International Biometric Society, vol. 64(1), pages 96-105, March.
- Fushing Hsieh & Yi-Kuan Tseng & Jane-Ling Wang, 2006. "Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited," Biometrics, The International Biometric Society, vol. 62(4), pages 1037-1043, December.
- Xiao Song & Marie Davidian & Anastasios A. Tsiatis, 2002. "A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 58(4), pages 742-753, December.
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- Method of the month: Shared parameter models
by Sam Watson in The Academic Health Economists' Blog on 2018-07-26 06:00:40
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Antonello Maruotti, 2015. "Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 84-109, March.
- Arnab Mukherji & Satrajit Roychowdhury & Pulak Ghosh & Sarah Brown, 2012. "Estimating Healthcare Demand for an Aging Population: A Flexible and Robust Bayesian Joint Model," Working Papers 2012027, The University of Sheffield, Department of Economics.
- Roula Tsonaka & Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre, 2010. "Nonignorable Models for Intermittently Missing Categorical Longitudinal Responses," Biometrics, The International Biometric Society, vol. 66(3), pages 834-844, September.
- Peter J. Diggle & Raquel Menezes & Ting-li Su, 2010. "Geostatistical inference under preferential sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 191-232.
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