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Analysis of Multivariate Longitudinal Outcomes With Nonignorable Dropouts and Missing Covariates: Changes in Methadone Treatment Practices

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  • Roy J.
  • Lin X.

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  • Roy J. & Lin X., 2002. "Analysis of Multivariate Longitudinal Outcomes With Nonignorable Dropouts and Missing Covariates: Changes in Methadone Treatment Practices," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 40-52, March.
    • Handle: RePEc:bes:jnlasa:v:97:y:2002:m:march:p:40-52
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    Cited by:

    1. Artz G. Luwanda & Henry G. Mwambi, 2016. "A Nonlinear Mixed-Effects Model for Multivariate Longitudinal Data with Dropout with Application to HIV Disease Dynamics," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(2), pages 277-294, June.
    2. Sun, Liuquan & Tong, Xingwei, 2009. "Analyzing longitudinal data with informative observation times under biased sampling," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1162-1168, May.
    3. Wan-Lun Wang, 2019. "Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 196-222, March.
    4. Mathieu Bunel & Jean-Pascal Guironnet, 2011. "Earning Inequalities Between and Within Nests," Working Papers halshs-00868198, HAL.
    5. Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
    6. Jean-Pascal Guironnet & Matthieu Bunel, 2011. "Earning Inequalities Between and Within Nests: A Multilevel Modeling Approach Applied to the Case of France," Economics Working Paper Archive (University of Rennes & University of Caen) 201118, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    7. Ming Ouyang & Xinyuan Song, 2020. "Bayesian Local Influence of Generalized Failure Time Models with Latent Variables and Multivariate Censored Data," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 298-316, July.
    8. 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.

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