FitCalibNpmle: Fitting Nonparametric Calibration Models

In daniel258/CoxBinChange: Cox Model with Interval-Censored Starting Time of a Covariate

Description

Fits a Weibull calibration model for time-to-exposure from interval-censored data. The exposure is a binary covariate measured in intermittent times.

Usage

FitCalibNpmle(w, w.res)

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

Value

The result of NPMLE model fitting for interval-censored data, as obtained by icenReg::ic_np

See Also

ic_np

Examples

# Simulate data set
sim.data <- ICcalib:::SimCoxIntervalCensSingle(n.sample = 200, lambda = 0.1, 
                                               alpha = 0.25, beta0 = log(0.5), 
                                               mu = 0.2, n.points = 2, 
                                               weib.shape = 1, weib.scale = 2)
# Calcualte the NPMLE for a nonparametric calibration model for the covariate 
# starting-time distribution
npmle.fit <- ICcalib::FitCalibNpmle(w = sim.data$w, w.res = sim.data$w.res)
# Plot the estimated survival function
plot(npmle.fit)

daniel258/CoxBinChange documentation built on May 14, 2019, 3:42 p.m.