CalcNpmleCalibP function

Calculating the probabilities of positive binary exposure status at a given time point using a nonparametric calibration model

For a given time point, calculate the probability of positive exposure value for multiple observations (participants). The function uses the results of a nonparametric calibration model fit, and given collected data on the history of the binary exposure for each participant.

CalcNpmleCalibP(w, w.res, point, fit.npmle)

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. Each measurement corresponds to the time points in w
• point: The time point at which the probabilities are estimated.
• fit.npmle: The result of icenReg::ic_np on the interval-censored data

Returns

A vector of estimated probabilities of positive exposure status at time point.

Examples

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 nonparametric calibration model
fit.npmle <- FitCalibNpmle(w = sim.data$w, w.res = sim.data$w.res)
# Calculate the conditional probabilities of binary covariate=1 at time one
probs <- CalcNpmleCalibP(w = sim.data$w, w.res = sim.data$w.res, 
                         point = 1, fit.npmle = fit.npmle)
summary(probs)