yppe: Fits the Yang and Prentice model with baseline distribution...

In YPPE: Yang and Prentice Model with Piecewise Exponential Baseline Distribution

Description

Fits the Yang and Prentice model with baseline distribution modelled by the piecewise exponential distribution.

Usage

yppe(
  formula,
  data,
  n_int = NULL,
  rho = NULL,
  tau = NULL,
  hessian = TRUE,
  approach = c("mle", "bayes"),
  hyper_parms = list(h1_gamma = 0, h2_gamma = 4, mu_psi = 0, sigma_psi = 4, mu_phi = 0,
    sigma_phi = 4, mu_beta = 0, sigma_beta = 4),
  ...
)

Arguments

formula	an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.
data	an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which yppe is called.
n_int	number of intervals of the PE distribution. If NULL, default value (square root of n) is used.
rho	the time grid of the PE distribution. If NULL, the function timeGrid is used to compute rho.
tau	the maximum time of follow-up. If NULL, tau = max(time), where time is the vector of observed survival times.
hessian	logical; If TRUE (default), the hessian matrix is returned when approach="mle".
approach	approach to be used to fit the model (mle: maximum likelihood; bayes: Bayesian approach).
hyper_parms	a list containing the hyper-parameters of the prior distributions (when approach = "bayes"). If not specified, default values are used.
...	Arguments passed to either 'rstan::optimizing' or 'rstan::sampling' .

Value

yppe returns an object of class "yppe" containing the fitted model.

Examples

# ML approach:
library(YPPE)
mle <- yppe(Surv(time, status)~arm, data=ipass, approach="mle")
summary(mle)

# Bayesian approach:
bayes <- yppe(Surv(time, status)~arm, data=ipass, approach="bayes")
summary(bayes)

YPPE documentation built on Jan. 10, 2020, 1:08 a.m.