bayesSurv

bayesSurv: Bayesian Survival Regression with Flexible Error and Random Effects Distributions. Contains Bayesian implementations of Mixed-Effects Accelerated Failure Time (MEAFT) models for censored data. Those can be not only right-censored but also interval-censored, doubly-interval-censored or misclassified interval-censored.


References in zbMATH (referenced in 9 articles , 1 standard article )

Showing results 1 to 9 of 9.
Sorted by year (citations)

  1. Gamage, Prabhashi W. Withana; McMahan, Christopher S.; Wang, Lianming; Tu, Wanzhu: A Gamma-frailty proportional hazards model for bivariate interval-censored data (2018)
  2. Rubio, F. J.; Steel, M. F. J.: Flexible linear mixed models with improper priors for longitudinal and survival data (2018)
  3. Christophe Genolini; Xavier Alacoque; Mariane Sentenac; Catherine Arnaud: kml and kml3d: R Packages to Cluster Longitudinal Data (2015) not zbMATH
  4. Wang, Naichen; Wang, Lianming; McMahan, Christopher S.: Regression analysis of bivariate current status data under the gamma-frailty proportional hazards model using the EM algorithm (2015)
  5. Yang, Mingan; Chen, Lihua; Dong, Guanghui: Semiparametric Bayesian accelerated failure time model with interval-censored data (2015)
  6. Lesaffre, Emmanuel; Declerck, Dominique: Oral health research: a source for innovative new statistical developments (2014)
  7. Romeo, Jose S.; Meyer, Renate; Reyes-Lopez, Felipe E.: Hierarchical failure time regression using mixtures for classification of the immune response of atlantic salmon (2014)
  8. Zhang, Jiajia; Lawson, Andrew B.: Bayesian parametric accelerated failure time spatial model and its application to prostate cancer (2011)
  9. Komárek, Arnošt; Lesaffre, Emmanuel: Bayesian accelerated failure time model for correlated interval-censored data with a normal mixture as error distribution (2007)