CoxBcv.rob: Uncorrected robust sandwich variance estimator

In CoxBcv: Bias-Corrected Sandwich Variance Estimators for Marginal Cox Analysis of Cluster Randomized Trials

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)

CoxBcv documentation built on March 18, 2022, 5:51 p.m.