Fitting Proportional Hazards Calibration Models with Covariates
Fitting Proportional Hazards Calibration Models with Covariates
Fits a proportional hazards calibration model for time-to-exposure from interval-censored data with covariates. The exposure is a binary covariate measured in intermittent times. The covariates (Q) are associated with the time-to-exposure.
FitCalibCox(w, w.res, Q, hz.times, n.int =5, order =2)
Arguments
w: A matrix of time points when measurements on the binary covariate were obtained.
w.res: A matrix of measurement results of the binary covariate. It corresponds to the time points in w
Q: Matrix of covariates for PH calibration model
hz.times: Times used for calculating the baseline hazard function from PH calibration model
n.int: The number of interior knots to be used, see ICsurv::fast.PH.ICsurv.EM, Default: 5
order: the order of the basis functions. See ICsurv::fast.PH.ICsurv.EM, Default: 2
Returns
An object created by ICsurv::fast.PH.ICsurv.EM, with additional variables knots and order.
Examples
sim.data <- ICcalib:::SimCoxIntervalCensCox(n.sample =200, lambda =0.1, alpha =0.25, beta0 =0, gamma.q = c(log(0.75), log(2.5)), gamma.z = log(1.5), mu =0.2, n.points =2)# The baseline hazard for the calibration model is calculated in observation timescox.hz.times <- sort(unique(sim.data$obs.tm))# Fit proprtional hazards calibration modelFitCalibCox(w = sim.data$w, w.res = sim.data$w.res, Q = sim.data$Q, hz.times = cox.hz.times, n.int =5, order =2)