Lifetime Data Analysis

, Volume 17, Issue 1, pp 37–42 | Cite as

Rejoinder for “Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches”

  • Wesley Johnson
  • Adam J. Branscum
  • Timothy E. Hanson
Open Access


Death Time Lifetime Data Anal Predictive Density Dirichlet Process Mixture Piecewise Exponential Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.


  1. Crespi CM, Boscardin WJ (2009) Bayesian model checking for multivariate outcome data. Comput Stat Data Anal 53: 3765–3772MATHCrossRefGoogle Scholar
  2. Ding J, Wang J-L (2008) Modeling longitudinal data with nonparametric multiplicative random effects jointly with survival data. Biometrics 64: 546–556MATHCrossRefMathSciNetGoogle Scholar
  3. Gelman A, Meng X-L, Stern H (1996) Posterior predictive assessment of model fitness via realized discrepancies. Stat Sin 66: 733–807MathSciNetGoogle Scholar
  4. Guo X., Carlin BP (2004) Separate and joint modeling of longitudinal and event time data using standard computer packages. Am Statist 58: 16–24CrossRefMathSciNetGoogle Scholar
  5. Hanson T, Johnson WO, Laud P (2009) Semiparametric inference for survival models with step process covariates. Can J Stat 37: 60–79MATHCrossRefMathSciNetGoogle Scholar
  6. Henderson R, Diggle P, Dobson A (2000) Joint modelling of longitudinal measurements and event time data. Biostatistics 1: 465–480MATHCrossRefGoogle Scholar
  7. Lemos RT, Sansó B (2009) A spatio-temporal model for mean, anomaly, and trend fields of north Atlantic sea surface temperature. J Am Stat Assoc 104: 5–18CrossRefGoogle Scholar
  8. Li Y, Lin X, Müller P (2010) Bayesian inference in semi-parametric mixed models for longitudinal data. Biometrics 66: 70–78MATHCrossRefGoogle Scholar
  9. Rizopoulos D, Verbeke G, Molenberghs G (2009) Multiple-imputation-based residuals and diagnostic plots for joint models of longitudinal and survival outcomes. Biometrics 66: 20–29CrossRefGoogle Scholar
  10. Sinharay S, Stern HS (2003) Posterior predictive model checking in hierarchical models. J Stat Plan Inference 111: 209–221MATHCrossRefMathSciNetGoogle Scholar
  11. Zhang S, Müller P, Do K-A (2010) A Bayesian semiparametric survival model with longitudinal markers. Biometrics 66: 435–443MATHCrossRefGoogle Scholar

Copyright information

© The Author(s) 2010

Authors and Affiliations

  • Wesley Johnson
    • 1
  • Adam J. Branscum
    • 2
  • Timothy E. Hanson
    • 3
  1. 1.Department of statisticsUniversity of california IrvineIrvineUSA
  2. 2.Departments of BiostatisticsStatistics and Epidemiology University of KentuckyLexingtonsUSA
  3. 3.Division of BiostatisticsUniversity of MinnesotaMinneapolisUSA

Personalised recommendations