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For: Huang Y, Dagne G, Wu L. Bayesian inference on joint models of HIV dynamics for time-to-event and longitudinal data with skewness and covariate measurement errors. Stat Med 2011;30:2930-46. [PMID: 21805486 DOI: 10.1002/sim.4321] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2010] [Accepted: 05/25/2011] [Indexed: 11/09/2022]
Number Cited by Other Article(s)
1
Chen J, Huang Y, Wang Q. Semiparametric multivariate joint model for skewed-longitudinal and survival data: A Bayesian approach. Stat Med 2023;42:4972-4989. [PMID: 37668072 DOI: 10.1002/sim.9896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/03/2023] [Accepted: 08/23/2023] [Indexed: 09/06/2023]
2
Tang J, Tang AM, Tang N. Variable selection for joint models of multivariate skew-normal longitudinal and survival data. Stat Methods Med Res 2023;32:1694-1710. [PMID: 37408456 DOI: 10.1177/09622802231181767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
3
Lin TI, Wang WL. Flexible modeling of multiple nonlinear longitudinal trajectories with censored and non-ignorable missing outcomes. Stat Methods Med Res 2023;32:593-608. [PMID: 36624626 DOI: 10.1177/09622802221146312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
4
Huang Y, Tang NS, Chen J. Multivariate piecewise joint models with random change-points for skewed-longitudinal and survival data. J Appl Stat 2022;49:3063-3089. [DOI: 10.1080/02664763.2021.1935797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
5
Huang Y, Chen J, Xu L, Tang NS. Bayesian Joint Modeling of Multivariate Longitudinal and Survival Data With an Application to Diabetes Study. Front Big Data 2022;5:812725. [PMID: 35574573 PMCID: PMC9094046 DOI: 10.3389/fdata.2022.812725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 03/24/2022] [Indexed: 11/15/2022]  Open
6
Mehdizadeh P, Baghfalaki T, Esmailian M, Ganjali M. A two-stage approach for joint modeling of longitudinal measurements and competing risks data. J Biopharm Stat 2021;31:448-468. [PMID: 33905295 DOI: 10.1080/10543406.2021.1918142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/30/2022]
7
Alizadehsani R, Roshanzamir M, Hussain S, Khosravi A, Koohestani A, Zangooei MH, Abdar M, Beykikhoshk A, Shoeibi A, Zare A, Panahiazar M, Nahavandi S, Srinivasan D, Atiya AF, Acharya UR. Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991-2020). ANNALS OF OPERATIONS RESEARCH 2021;339:1-42. [PMID: 33776178 PMCID: PMC7982279 DOI: 10.1007/s10479-021-04006-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/23/2021] [Indexed: 05/17/2023]
8
Zhang H, Huang Y. Bayesian joint modeling for partially linear mixed-effects quantile regression of longitudinal and time-to-event data with limit of detection, covariate measurement errors and skewness. J Biopharm Stat 2020;31:295-316. [PMID: 33284096 DOI: 10.1080/10543406.2020.1852248] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
9
Chen J, Huang Y, Tang NS. Bayesian Change-Point Joint Models for Multivariate Longitudinal and Time-to-Event Data. Stat Biopharm Res 2020. [DOI: 10.1080/19466315.2020.1837234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
10
Lin TI, Wang WL. Multivariate-t linear mixed models with censored responses, intermittent missing values and heavy tails. Stat Methods Med Res 2020;29:1288-1304. [PMID: 31242813 DOI: 10.1177/0962280219857103] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
11
Alsefri M, Sudell M, García-Fiñana M, Kolamunnage-Dona R. Bayesian joint modelling of longitudinal and time to event data: a methodological review. BMC Med Res Methodol 2020;20:94. [PMID: 32336264 PMCID: PMC7183597 DOI: 10.1186/s12874-020-00976-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 04/12/2020] [Indexed: 02/07/2023]  Open
12
Zhang H, Huang Y. Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study. LIFETIME DATA ANALYSIS 2020;26:339-368. [PMID: 31140028 DOI: 10.1007/s10985-019-09478-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Accepted: 05/23/2019] [Indexed: 06/09/2023]
13
Furgal AKC, Sen A, Taylor JMG. Review and Comparison of Computational Approaches for Joint Longitudinal and Time-to-Event Models. Int Stat Rev 2019;87:393-418. [PMID: 32042217 PMCID: PMC7009936 DOI: 10.1111/insr.12322] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 02/25/2019] [Indexed: 12/15/2022]
14
Lu T, Lu M, Wang M, Zhang J, Dong GH, Xu Y. Partially linear mixed-effects joint models for skewed and missing longitudinal competing risks outcomes. J Biopharm Stat 2017;29:971-989. [PMID: 29252088 DOI: 10.1080/10543406.2017.1378663] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
15
Zhang H, Huang Y, Wang W, Chen H, Langland-Orban B. Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features. Stat Methods Med Res 2017;28:569-588. [PMID: 28936916 DOI: 10.1177/0962280217730852] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
16
Lu T. Modeling Longitudinal-Competing Risks Data With Skew Distribution and Mismeasured Covariate. Stat Biopharm Res 2017. [DOI: 10.1080/19466315.2016.1208624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
17
Tang AM, Tang NS, Zhu H. Influence analysis for skew-normal semiparametric joint models of multivariate longitudinal and multivariate survival data. Stat Med 2017;36:1476-1490. [DOI: 10.1002/sim.7211] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 11/04/2016] [Accepted: 12/01/2016] [Indexed: 11/07/2022]
18
Tang AM, Zhao X, Tang NS. Bayesian variable selection and estimation in semiparametric joint models of multivariate longitudinal and survival data. Biom J 2016;59:57-78. [DOI: 10.1002/bimj.201500070] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2015] [Revised: 02/01/2016] [Accepted: 02/16/2016] [Indexed: 11/12/2022]
19
Bayesian inference on partially linear mixed-effects joint models for longitudinal data with multiple features. Comput Stat 2016. [DOI: 10.1007/s00180-016-0671-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
20
Huang Y, Dagne GA, Park JG. Mixture Joint Models for Event Time and Longitudinal Data With Multiple Features. Stat Biopharm Res 2016. [DOI: 10.1080/19466315.2016.1142891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
21
Yang L, Yu M, Gao S. Joint Models for Multiple Longitudinal Processes and Time-to-event Outcome. J STAT COMPUT SIM 2016;86:3682-3700. [PMID: 27920466 DOI: 10.1080/00949655.2016.1181760] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
22
Yang L, Yu M, Gao S. Prediction of coronary artery disease risk based on multiple longitudinal biomarkers. Stat Med 2016;35:1299-314. [PMID: 26439685 PMCID: PMC5024352 DOI: 10.1002/sim.6754] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Revised: 09/11/2015] [Accepted: 09/14/2015] [Indexed: 01/05/2023]
23
Wang WL, Lin TI, Lachos VH. Extending multivariate- t linear mixed models for multiple longitudinal data with censored responses and heavy tails. Stat Methods Med Res 2015;27:48-64. [PMID: 26668091 DOI: 10.1177/0962280215620229] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
24
Lawrence Gould A, Boye ME, Crowther MJ, Ibrahim JG, Quartey G, Micallef S, Bois FY. Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working group. Stat Med 2015;34:2181-95. [PMID: 24634327 PMCID: PMC4677775 DOI: 10.1002/sim.6141] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Accepted: 02/19/2014] [Indexed: 12/25/2022]
25
Lu T, Wang M, Liu G, Dong GH, Qian F. Mixed-effects varying-coefficient model with skewed distribution coupled with cause-specific varying-coefficient hazard model with random-effects for longitudinal-competing risks data analysis. J Biopharm Stat 2015;26:519-33. [PMID: 26097990 DOI: 10.1080/10543406.2015.1052493] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
26
Huang Y. Quantile regression-based Bayesian semiparametric mixed-effects models for longitudinal data with non-normal, missing and mismeasured covariate. J STAT COMPUT SIM 2015. [DOI: 10.1080/00949655.2015.1057732] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
27
Chen J, Huang Y. A Bayesian mixture of semiparametric mixed-effects joint models for skewed-longitudinal and time-to-event data. Stat Med 2015;34:2820-43. [PMID: 25924891 DOI: 10.1002/sim.6517] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Revised: 02/19/2015] [Accepted: 04/04/2015] [Indexed: 11/07/2022]
28
Lu T, Huang Y. Bayesian inference on mixed-effects varying-coefficient joint models with skew- t distribution for longitudinal data with multiple features. Stat Methods Med Res 2015;26:1146-1164. [PMID: 25670749 DOI: 10.1177/0962280215569294] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
29
Chen H, Huang Y, Zhang N. Joint modeling of a linear mixed effects model for selfesteem from mean ages 13 to 22 and a generalized linear model for anxiety disorder at mean age 33. ACTA ACUST UNITED AC 2015. [DOI: 10.7243/2053-7662-3-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
30
Arbeev KG, Akushevich I, Kulminski AM, Ukraintseva SV, Yashin AI. Joint Analyses of Longitudinal and Time-to-Event Data in Research on Aging: Implications for Predicting Health and Survival. Front Public Health 2014;2:228. [PMID: 25414844 PMCID: PMC4222133 DOI: 10.3389/fpubh.2014.00228] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2014] [Accepted: 10/24/2014] [Indexed: 12/23/2022]  Open
31
Jointly modeling time-to-event and longitudinal data: A Bayesian approach. STAT METHOD APPL-GER 2013;23:95-121. [PMID: 24611039 DOI: 10.1007/s10260-013-0242-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
32
McCrink LM, Marshall AH, Cairns KJ. Advances in Joint Modelling: A Review of Recent Developments with Application to the Survival of End Stage Renal Disease Patients. Int Stat Rev 2013. [DOI: 10.1111/insr.12018] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
33
Analysis of Longitudinal and Survival Data: Joint Modeling, Inference Methods, and Issues. JOURNAL OF PROBABILITY AND STATISTICS 2012. [DOI: 10.1155/2012/640153] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]  Open
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