R: Prediction in Joint Models

survfitJMMLSM {JMH}

R Documentation

Prediction in Joint Models

Description

This function computes the conditional probability of surviving later times than the last observed time for which a longitudinal measurement was available.

Usage

survfitJMMLSM(
  object,
  seed = 100,
  ynewdata = NULL,
  cnewdata = NULL,
  u = NULL,
  Last.time = NULL,
  obs.time = NULL,
  method = c("Laplace", "GH"),
  quadpoint = NULL,
  ...
)

Arguments

`object`	an object inheriting from class `JMMLSM`.
`seed`	a random seed number to proceed non-parametric bootstrap. Default is 100.
`ynewdata`	a data frame that contains the longitudinal and covariate information for the subjects for which prediction of survival probabilities is required.
`cnewdata`	a data frame that contains the survival and covariate information for the subjects for which prediction of survival probabilities is required.
`u`	a numeric vector of times for which prediction survival probabilities are to be computed.
`Last.time`	a numeric vector or character string. This specifies the known time at which each of the subjects in cnewdata was known to be alive. If NULL, then this is automatically taken as the survival time of each subject. If a numeric vector, then it is assumed to be greater than or equals to the last available longitudinal time point for each subject. If a character string, then it should be a variable in cnewdata.
`obs.time`	a character string of specifying a longitudinal time variable in ynewdata.
`method`	a character string specifying the type of probability approximation; if `Laplace`, then a first order estimator is computed. If `GH`, then the standard Gauss-Hermite quadrature is used instead.
`quadpoint`	number of quadrature points used for estimating conditional probabilities when `method = "GH"`. Default is NULL. If `method = "GH"`, then 15 is used.
`...`	further arguments passed to or from other methods.

Value

a list of matrices with conditional probabilities for subjects.

Author(s)