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Journal of Applied Statistics Volume 42, 2015 - Issue 10
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Original Articles

Joint modeling of mixed skewed continuous and ordinal longitudinal responses: a Bayesian approach

M. TeimourianDepartment of Mathematics and Statistics, Roudehen Branch, Islamic Azad University, Roudehen, Iran
,
T. BaghfalakiDepartment of Statistics, Faculty of Mathematical Sciences, Tarbiat Modares University, Tehran, IranCorrespondence[email protected]
,
M. GanjaliDepartment of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
&
D. BerridgeFarr Institute-CIPHER, College of Medicine, Sawnsea University, Swansea, Wales, UK
Pages 2233-2256 | Received 22 May 2013, Accepted 23 Feb 2015, Published online: 27 Mar 2015

Citations (9)

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Seyede Sedighe Azimi, Ehsan Bahrami Samani & Mojtaba Ganjali. (2022) Analysis of mixed correlated overdispersed binomial and ordinal longitudinal responses: LogLindley-Binomial and ordinal random effects model. Journal of Applied Statistics 49:7, pages 1742-1768.
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T. Baghfalaki, M. Ganjali, A. Kabir & A. Pazouki. (2022) A Bayesian shared parameter model for joint modeling of longitudinal continuous and binary outcomes. Journal of Applied Statistics 49:3, pages 638-655.
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Taban Baghfalaki, Shiva Kalantari, Mojtaba Ganjali, Farzad Hadaegh & Bagher Pahlavanzadeh. (2020) Bayesian joint modeling of ordinal longitudinal measurements and competing risks survival data for analysing Tehran Lipid and Glucose Study. Journal of Biopharmaceutical Statistics 30:4, pages 689-703.
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Siamak Ghasemzadeh, Mojtaba Ganjali & Taban Baghfalaki. (2020) Bayesian quantile regression for joint modeling of longitudinal mixed ordinal and continuous data. Communications in Statistics - Simulation and Computation 49:2, pages 375-395.
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S. Ghasemzadeh, M. Ganjali & T. Baghfalaki. (2018) A Bayesian conditional model for bivariate mixed ordinal and skew continuous longitudinal responses using quantile regression. Journal of Applied Statistics 45:14, pages 2619-2642.
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Articles from other publishers (4)

Nicholas Seedorff, Grant Brown, Breanna Scorza & Christine A. Petersen. (2022) Joint Bayesian longitudinal models for mixed outcome types and associated model selection techniques. Computational Statistics 38:4, pages 1735-1769.
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Taban Baghfalaki & Mojtaba Ganjali. (2019) A transition model for analyzing multivariate longitudinal data using Gaussian copula approach. AStA Advances in Statistical Analysis 104:2, pages 169-223.
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Zhihua MaGuanghui Chen. (2019) Bayesian semiparametric latent variable model with DP prior for joint analysis: Implementation with nimble. Statistical Modelling 20:1, pages 71-95.
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O.D. Buhule, A.S. Wahed & A.O. Youk. (2017) Bayesian hierarchical joint modeling of repeatedly measured continuous and ordinal markers of disease severity: Application to Ugandan diabetes data. Statistics in Medicine 36:29, pages 4677-4691.
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