partsurv: Fit partitioned survival model to survival data

View source: R/survival_functions.R

partsurvR Documentation

Fit partitioned survival model to survival data

Description

partsurv fits partitioned survival model to survival data.

Usage

partsurv(
  pfs_survHE = NULL,
  os_survHE = NULL,
  l_d.data = NULL,
  l_vc.data = NULL,
  par = FALSE,
  chol = FALSE,
  choose_PFS = NULL,
  choose_OS = NULL,
  time = times,
  v_names_states,
  PA = FALSE,
  n_sim = 100,
  seed = 421,
  warn = TRUE,
  dat.x = 0
)

Arguments

pfs_survHE

survHE obj fitting PFS.

os_survHE

survHE obj fitting OS.

l_d.data

list of mean parameter estimates (list containing 2 numerical estimates, 1st being for PFS and 2nd being for OS).

l_vc.data

list of variance-covariance matrices (or their Cholesky decomposition) of parameter estimates (list containing 2 matrices, 1st being for PFS and 2nd being for OS).

par

set to TRUE if parameter mean estimates and their variance-covariance matrices are used instead of survHE objects. Default = FALSE

chol

set to TRUE if l_vc.data contains Cholesky decomposition of the variance-covariance matrices instead of the actual variance-covariance matrices. Default = FALSE

choose_PFS

chosen PFS distribution. Choose from: Exponential, Weibull (AFT), Gamma, log-Normal, log-Logistic, Gompertz, Exponential Cure, Weibull (AFT) Cure, Gamma Cure, log-Normal Cure, log-Logistic Cure, Gompertz Cure.

choose_OS

chosen OS distribution. Choose from: Exponential, Weibull (AFT), Gamma, log-Normal, log-Logistic, Gompertz, Exponential Cure, Weibull (AFT) Cure, Gamma Cure, log-Normal Cure, log-Logistic Cure, Gompertz Cure.

time

numeric vector of time to estimate probabilities.

v_names_states

vector of state names.

PA

run probabilistic analysis. Default = FALSE.

n_sim

number of PA simulations. Default = 100.

seed

seed for random number generation. Default = 421.

warn

prints a warning message whenever PFS > OS

Value

a list containing Markov trace, expected survival, survival probabilities, transition probabilities.


DARTH-git/darthtools documentation built on April 3, 2025, 2:12 p.m.