Description
joineRML is an extension of the joineR package for fitting joint
models of time-to-event data and multivariate longitudinal data. The model
fitted in joineRML is an extension of the Wulfsohn and Tsiatis (1997) and
Henderson et al. (2000) models, which is comprised on \((K +
1)\)-sub-models: a Cox proportional hazards regression model (Cox, 1972) and
a \(K\)-variate linear mixed-effects model - a direct extension of the
Laird and Ware (1982) regression model. The model is fitted using a Monte
Carlo Expectation-Maximization (MCEM) algorithm, which closely follows the
methodology presented by Lin et al. (2002).References
Wulfsohn MS, Tsiatis AA. A joint model for survival and longitudinal data
measured with error. Biometrics. 1997; 53(1): 330-339. Henderson R, Diggle PJ, Dobson A. Joint modelling of longitudinal
measurements and event time data. Biostatistics. 2000; 1(4):
465-480. Cox DR. Regression models and life-tables. J R Stat Soc Ser B Stat
Methodol. 1972; 34(2): 187-220. Laird NM, Ware JH. Random-effects models for longitudinal data.
Biometrics. 1982; 38(4): 963-974.