CoxBcv.rob {CoxBcv} | R Documentation |
Uncorrected robust sandwich variance estimator
Description
Calculate the uncorrected robust sandwich variance estimator for marginal Cox analysis of cluster randomized trials (Spiekerman and Lin, 1998).
Usage
CoxBcv.rob(Y, Delta, X, ID)
Arguments
Y |
vector of observed time-to-event data. |
Delta |
vector of censoring indicators. |
X |
matrix of marginal mean covariates with one column for one covariate (design matrix excluding intercept). |
ID |
vector of cluster identifiers. |
Value
coef - estimate of coefficients.
exp(coef) - estimate of hazard ratio.
ROB-var - uncorrected robust sandwich variance estimate of coef.
References
Spiekerman, C. F., & Lin, D. Y. (1998). Marginal regression models for multivariate failure time data. Journal of the American Statistical Association, 93(443), 1164-1175.
Examples
Y <- c(11,19,43,100,7,100,100,62,52,1,7,6)
Delta <- c(1,1,1,0,1,0,0,1,1,1,1,1)
X1 <- c(0,0,0,0,0,0,1,1,1,1,1,1)
X2 <- c(-19,6,-25,48,10,-25,15,22,17,-9,45,12)
ID <- c(1,1,2,2,3,3,4,4,5,5,6,6)
X <- X1
CoxBcv.rob(Y,Delta,X,ID)
X <- cbind(X1,X2)
CoxBcv.rob(Y,Delta,X,ID)
[Package CoxBcv version 0.0.1.0 Index]