These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
232 related articles for article (PubMed ID: 21213341)
1. Joint modeling of survival time and longitudinal data with subject-specific changepoints in the covariates. Tapsoba Jde D; Lee SM; Wang CY Stat Med; 2011 Feb; 30(3):232-49. PubMed ID: 21213341 [TBL] [Abstract][Full Text] [Related]
2. Semiparametric approaches for joint modeling of longitudinal and survival data with time-varying coefficients. Song X; Wang CY Biometrics; 2008 Jun; 64(2):557-66. PubMed ID: 17725812 [TBL] [Abstract][Full Text] [Related]
3. Improving efficiency using the Rao-Blackwell theorem in corrected and conditional score estimation methods for joint models. Huang YH; Hwang WH; Chen FY Biometrics; 2016 Dec; 72(4):1136-1144. PubMed ID: 26953722 [TBL] [Abstract][Full Text] [Related]
4. A flexible B-spline model for multiple longitudinal biomarkers and survival. Brown ER; Ibrahim JG; DeGruttola V Biometrics; 2005 Mar; 61(1):64-73. PubMed ID: 15737079 [TBL] [Abstract][Full Text] [Related]
5. Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach. Faucett CL; Thomas DC Stat Med; 1996 Aug; 15(15):1663-85. PubMed ID: 8858789 [TBL] [Abstract][Full Text] [Related]
6. A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data. Song X; Davidian M; Tsiatis AA Biometrics; 2002 Dec; 58(4):742-53. PubMed ID: 12495128 [TBL] [Abstract][Full Text] [Related]
7. Joint modeling of longitudinal data and informative dropout time in the presence of multiple changepoints. Ghosh P; Ghosh K; Tiwari RC Stat Med; 2011 Mar; 30(6):611-26. PubMed ID: 21337357 [TBL] [Abstract][Full Text] [Related]
8. Bayesian inference on mixed-effects location scale models with skew-t distribution and mismeasured covariates for longitudinal data. Lu T Stat Med; 2017 Jul; 36(16):2614-2629. PubMed ID: 28421622 [TBL] [Abstract][Full Text] [Related]
10. Hierarchical mixture models for longitudinal immunologic data with heterogeneity, non-normality, and missingness. Huang Y; Chen J; Yin P Stat Methods Med Res; 2017 Feb; 26(1):223-247. PubMed ID: 25038070 [TBL] [Abstract][Full Text] [Related]
11. A corrected pseudo-score approach for additive hazards model with longitudinal covariates measured with error. Song X; Huang Y Lifetime Data Anal; 2006 Mar; 12(1):97-110. PubMed ID: 16583301 [TBL] [Abstract][Full Text] [Related]
12. Partially linear mixed-effects joint models for skewed and missing longitudinal competing risks outcomes. Lu T; Lu M; Wang M; Zhang J; Dong GH; Xu Y J Biopharm Stat; 2019; 29(6):971-989. PubMed ID: 29252088 [TBL] [Abstract][Full Text] [Related]
13. On corrected score approach for proportional hazards model with covariate measurement error. Song X; Huang Y Biometrics; 2005 Sep; 61(3):702-14. PubMed ID: 16135021 [TBL] [Abstract][Full Text] [Related]
14. A Copula Approach to Joint Modeling of Longitudinal Measurements and Survival Times Using Monte Carlo Expectation-Maximization with Application to AIDS Studies. Ganjali M; Baghfalaki T J Biopharm Stat; 2015; 25(5):1077-99. PubMed ID: 25372017 [TBL] [Abstract][Full Text] [Related]
15. Jointly Modeling Event Time and Skewed-Longitudinal Data with Missing Response and Mismeasured Covariate for AIDS Studies. Huang Y; Yan C; Xing D; Zhang N; Chen H J Biopharm Stat; 2015; 25(4):670-94. PubMed ID: 24905593 [TBL] [Abstract][Full Text] [Related]
16. Approximate nonparametric corrected-score method for joint modeling of survival and longitudinal data measured with error. Tapsoba JD; Lee SM; Wang CY Biom J; 2011 Jul; 53(4):557-77. PubMed ID: 21717494 [TBL] [Abstract][Full Text] [Related]
17. A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects. Huang X; Li G; Elashoff RM; Pan J Lifetime Data Anal; 2011 Jan; 17(1):80-100. PubMed ID: 20549344 [TBL] [Abstract][Full Text] [Related]
18. Joint modeling of longitudinal continuous, longitudinal ordinal, and time-to-event outcomes. Alam K; Maity A; Sinha SK; Rizopoulos D; Sattar A Lifetime Data Anal; 2021 Jan; 27(1):64-90. PubMed ID: 33236257 [TBL] [Abstract][Full Text] [Related]
19. Data generation for the Cox proportional hazards model with time-dependent covariates: a method for medical researchers. Hendry DJ Stat Med; 2014 Feb; 33(3):436-54. PubMed ID: 24014094 [TBL] [Abstract][Full Text] [Related]
20. Joint modeling of longitudinal and survival data with missing and left-censored time-varying covariates. Chen Q; May RC; Ibrahim JG; Chu H; Cole SR Stat Med; 2014 Nov; 33(26):4560-76. PubMed ID: 24947785 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]