DESCRIPTION

Package: survtd
Version: 0.0.1
Title: Survival analysis with time-dependent covariates
Authors@R: c(person("Margarita", "Moreno-Betancur", email = "margarita.moreno@mcri.edu.au", role = c("cre","aut")),
             person("Samuel L", "Brilleman", role = c("ctb")))
Depends: R (>= 3.1.0), lme4, survival, timereg, mice
Imports: boot, ipw, stringr, MASS, Matrix
Description: Fit semi-parametric Cox or additive hazards regression models with time-
             fixed covariates of any type and multiple continuous time-dependent covariates 
             subject to missing data, measurement error or simply observed in discrete time: 
             all these issues are handled with the two-stage Multiple Imputation for
             Joint Modeling (MIJM) approach developed by Moreno-Betancur et al. (2017). 
             The package also provides easy-to-use implementations of an unadapted version
             (unMIJM); a simple two-stage approach (simple2S), based on single imputation 
             of the continuous markers from linear mixed models; and the last observation 
             carried forward (LOCF) approach for time-dependent covariates of any type, 
             which is the traditional method to incoporate these in hazard models. 
             Data simulation functions also included.
License: GPL (>= 3)
LazyData: TRUE
RoxygenNote: 6.0.1
Author: Margarita Moreno-Betancur [cre, aut],
  Samuel L Brilleman [ctb]
Maintainer: Margarita Moreno-Betancur <margarita.moreno@mcri.edu.au>