Description Usage Arguments Details Value See Also Examples
For a given time point, calculate the probability of positive exposure value for multiple observations (participants). The function uses the results of a Weibull calibration model fit, and given collected data on the history of the binary exposure for each participant.
1 | CalcWeibullRSP(w, w.res, point, weib.params)
|
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 |
point |
The time point at which the probabilities are estimated. |
weib.params |
A bivariate vector. Shape and scale parameters of the Weibull calibration model. |
At its present form this function is identical to CalcWeibullCalibP
. This is because the current version of the ICcalib
package
(Version 1.0.005), the user loop over the main event times. Then, at each event time point, the user should include the appropriate Weibull
parameters as estimated by FitCalibWeibullRS
.
A vector of estimated probabilities of positive exposure status at time point
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # 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)
case.times <- sim.data$obs.tm[sim.data$delta==1]
# Fit Weibull risk-set calibration models
calib.weib.params <- FitCalibWeibullRS(w = sim.data$w, w.res = sim.data$w.res,
tm = sim.data$obs.tm,
event = sim.data$delta)
# Calculate the conditional probabilities of binary covariate=1 at time one
probs <- CalcWeibullRSP(w = sim.data$w, w.res = sim.data$w.res, point = 1,
weib.params = calib.weib.params)
summary(probs)
## Not run:
if(interactive()){
#EXAMPLE1
}
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.