simData4iCoxph {intsurv} | R Documentation |
Simulated Survival Data with Uncertain Records
Description
Generate survival data with uncertain records. An integrative Cox model can
be fitted for the simulated data by function iCoxph
.
Usage
simData4iCoxph(
nSubject = 1000,
beta0Vec,
xMat,
maxNum = 2,
nRecordProb = c(0.9, 0.1),
matchCensor = 0.1,
matchEvent = 0.1,
censorMin = 0.5,
censorMax = 12.5,
lambda = 0.005,
rho = 0.7,
fakeLambda1 = lambda * exp(-3),
fakeRho1 = rho,
fakeLambda2 = lambda * exp(3),
fakeRho2 = rho,
mixture = 0.5,
randomMiss = TRUE,
eventOnly = FALSE,
...
)
Arguments
nSubject |
Number of subjects. |
beta0Vec |
Time-invariant covariate coefficients. |
xMat |
Design matrix. By default, three continuous variables following standard normal distribution and one binary variable following Bernoulli distribution with equal probability are used. |
maxNum |
Maximum number of uncertain records. |
nRecordProb |
Probability of the number of uncertain records. |
matchCensor |
The matching rate for subjects actually having censoring times. |
matchEvent |
The matching rate for subjects actually having event times. |
censorMin |
The lower boundary of the uniform distribution for generating censoring time. |
censorMax |
The upper boundary of the uniform distribution for generating censoring time. |
lambda |
A positive number, scale parameter in baseline rate function for true event times. |
rho |
A positive number, shape parameter in baseline rate function for true event times. |
fakeLambda1 |
A positive number, scale parameter in baseline rate function for fake event times from one distribution. |
fakeRho1 |
A positive number, shape parameter in baseline rate function for fake event times from one distribution. |
fakeLambda2 |
A positive number, scale parameter in baseline rate function for fake event times from another distribution. |
fakeRho2 |
A positive number, shape parameter in baseline rate function for fake event times from another distribution. |
mixture |
The mixture weights, i.e., the probabilities (summing up to one) of fake event times coming from different mixture components. |
randomMiss |
A logical value specifying whether the labels of the true
records are missing completely at random (MCAR) or missing not at random
(MNAR). The default value is |
eventOnly |
A logical value specifying whether the uncertain records
only include possible events. The default value is |
... |
Other arguments for future usage. |
Details
The event times are simulated from a Weibull proportional hazard model of given shape and baseline scale. The censoring times follow uniform distribution of specified boundaries.
Value
A data frame with the following columns,
-
ID
: subject ID -
time
: observed event times -
event
: event indicators -
isTure
: latent labels indicating the true records
and the corresponding covariates.
Examples
## See examples of function iCoxph