msm_frydman {icmstate} | R Documentation |
Determine NPMLE for Multi State illness death Markov model using Frydman (1995)
Description
Determine NPMLE for Multi State illness death Markov model using Frydman (1995)
Usage
msm_frydman(data, tol = 1e-08)
Arguments
data |
A
|
tol |
Tolerance of the EM algorithm. Algorithm will stop when the absolute difference between current mass estimates and new estimates is smaller than the tolerance |
Details
For an illness death model (1 = healthy, 2 = ill, 3 = dead) estimate the NPMLE in the following form:
F12
:Cumulative distribution function of 1->2 transition;
F13
:Cumulative distribution function of 1->3 transition;
Lambda23
:Cumulative intensity of 2->3 transition;
Value
A list with the following entries:
data_idx
:A list containing the data used for the fit (
matdata
), the indices for which group a subject belongs to (GroupX_idx
), some computational parameters (see Frydman(1995)) and the unique failure times of the 2->3 and 1->3 transitions respectively int_n_star
ande_k_star
;supportMSM
:A list containing all transition intervals in
A
and the theoretical support intervals inQ_mat
;z_lambda
:Computational quantities, see Frydman(1995);
cdf
:A list of functions that allow to recover the cdf for the 1->3 (
F13
) and 1->2 (F12
) transition and the cumulative hazard for the 2->3 (Lambda23
) transition.;
References
Frydman, H. (1995). Nonparametric Estimation of a Markov 'Illness-Death' Process from Interval- Censored Observations, with Application to Diabetes Survival Data. Biometrika, 82(4), 773-789. doi:10.2307/2337344
Examples
data <- data.frame(delta = c(0, 0, 1, 1), Delta = c(0, 1, 0, 1),
L = c(NA, NA, 1, 1.5), R = c(NA, 3, 2, 3),
time = c(4, 5, 6, 7))
mod_frydman <- msm_frydman(data)
visualise_data(data, mod_frydman)