CaseCohortIC {ICODS} | R Documentation |
Case-Cohort Studies with Interval-Censored Failure Time Data
Description
Provides a sieve semiparametric likelihood approach under the proportional hazards model for analyzing data from a case-cohort design with failure times subject to interval-censoring. The likelihood function is constructed using inverse probability weighting, and the sieves are built with Bernstein polynomials. A weighted bootstrap procedure is implemented for variance estimation.
Usage
CaseCohortIC(U, V, del1, del2, xi, z, sp, mVal, B, beta = NULL,
maxit = 10L, verbose = TRUE, ...)
Arguments
U |
numeric vector (n); examination time. See Details for further information. |
V |
numeric vector (n); examination time. See Details for further information. |
del1 |
integer vector (n); indicator of a left-censored observation I(T<=U). See Details for further information. |
del2 |
integer vector (n); indicator of an interval-censored observation I(U<T<=V). See Details for further information. |
xi |
integer vector (n); indicating membership of the case-cohort sample. |
z |
matrix (nxp); covariates. |
sp |
numeric (1); sampling probability 0 < sp < 1. |
mVal |
integer vector (m); one or more options for the degree of the Bernstein polynomials. If more than one option provided, the value resulting in the lowest AIC is selected. The results returned are for only that m-value. |
B |
integer (1); number of bootstrap samples used to calculate the variance estimate. |
beta |
numeric vector (p); initial values for beta. If NULL, initial guess set to 0.5 for each of the p parameters. |
maxit |
integer(1); maximum number of calls to optimization method. |
verbose |
logical; TRUE generates progress screen prints. |
... |
optional inputs to "control" of function optim(). |
Details
The implementation uses stats::optim() to minimize the likelihood. The hard-coded method is "BFGS". Users are able to make changes to the 'control' input of optim() by passing named inputs through the ellipses. If a call to optim() returns convergence = 1, i.e., optim() reached its internal maximum number of iterations before convergence was attained, the software automatically repeats the call to optim() with input variable par set to the last parameter values. This procedure is repeated at most maxit times.
Input parameters U, V, del1, and del2 are defined as follows. Suppose there are K follow-up examinations at times TE = (T1, T2, ..., TK), and the failure time is denoted as TF. For left-censored data, the failure occurs prior to the first follow-up examination (TF < T1); therefore, define U = T1, V = tau, and (del1,del2)=(1,0). For right-censored data, the failure has not yet occurred at the last follow-up examination (TF > TK); therefore, define U = 0, V = TK, and (del1,del2)=(0,0). For interval-censored data, the failure occurs between two follow-up examinations, e.g. T2 < TF < T3; therefore, define U and V to be the two consecutive follow-up examination times bracketing the failure time TF and (del1,del2)=(0,1).
Value
an object of class CaseCohort (inheriting from ICODS) containing
optim |
a list of the results returned by optim(). |
beta |
the estimated beta parameters. |
se |
the standard error of the estimated beta parameters. |
pValue |
the p-value of the estimated beta parameters. |
m |
the selected degree of the Bernstein polynomials. |
AIC |
the AIC value for the selected degree of the Bernstein polynomials. |
References
Zhou, Q., Zhou, H., and Cai, J. (2017). Case-cohort studies with interval-censored failure time data. Biometrika, 104(1): 17–29. <doi:10.1093/biomet/asw067>
Examples
data(ccData)
result <- CaseCohortIC(U = ccData$U,
V = ccData$V,
del1 = ccData$del1,
del2 = ccData$del2,
xi = ccData$xi,
z = ccData$z,
sp = 0.2,
mVal = 1L,
B = 10L,
beta = NULL,
maxit = 10L,
verbose = TRUE)
print(result)
mVal(result)
estimate(result)
optimObj(result)
minAIC(result)
summary(result)