Fitting Weibull Risk-Set Calibration Models
Fits Weibull risk-set calibration models for time-to-exposure from interval-censored data. The exposure is a binary covariate measured in intermittent times. This function fits a calibration model at each main event time point, using only members of the risk set at that time point.
FitCalibWeibullRS(w, w.res, tm, event, lower = 1e-04, upper = 200)
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. Each measurement corresponds to the time points in w
tm
: Vector of observed main event time or censoring time.event
: Vector of censoring indicators. 1
for event 0
for censoredlower
: A value to replace zero in the left point of the interval, Default: 1e-04upper
: A value to replace infinity in the right point of the interval, Default: 200A 2-column matrix with the shape and scale parameter for each time-point at which a calibration model was fitted.
In case of an error in the model-fitting at a certain time point, a Weibull calibration model is fitted and used for that time point.
# 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) # Fit Weibull risk-set calibration models for the conditional covariate # starting-time distributions ICcalib::FitCalibWeibullRS(w = sim.data$w, w.res = sim.data$w.res, tm = sim.data$obs.tm, event = sim.data$delta)
fitdistcens
, FitCalibWeibull
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