View source: R/survival_functions.R
partsurv | R Documentation |
partsurv
fits partitioned survival model to survival data.
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
)
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 |
a list containing Markov trace, expected survival, survival probabilities, transition probabilities.
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