CoxBcv.fg: Fay and Graubard (FG) bias-corrected sandwich variance...

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

Fay and Graubard (FG) bias-corrected sandwich variance estimator

Description

Calculate the Fay and Graubard (FG; 2001) bias-corrected sandwich variance estimator, for marginal Cox analysis of cluster randomized trials, proposed by Wang et al. (under review).

Usage

CoxBcv.fg(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.

• FG-var - FG bias-corrected sandwich variance estimate of coef.

References

Fay, M. P., & Graubard, B. I. (2001). Small‐sample adjustments for Wald‐type tests using sandwich estimators. Biometrics, 57(4), 1198-1206.

Wang, X., Turner, E. L., & Li, F. Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials. Under Review.

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.fg(Y,Delta,X,ID)

X <- cbind(X1,X2)
CoxBcv.fg(Y,Delta,X,ID)

XueqiWang/CoxBcv_R_package documentation built on April 2, 2022, 11:57 p.m.