R: Fitting Proportional Hazards Calibration Models with...

FitCalibCox {ICcalib}

R Documentation

Fitting Proportional Hazards Calibration Models with Covariates

Description

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.

Usage

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

Value

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 times
cox.hz.times <- sort(unique(sim.data$obs.tm)) 
# Fit proprtional hazards calibration model
FitCalibCox(w = sim.data$w, w.res = sim.data$w.res, Q = sim.data$Q, 
            hz.times = cox.hz.times, n.int = 5, order = 2)