CoxBcv.mbnmr: Hybrid MBNMR bias-corrected sandwich variance estimator

View source: R/CoxBcv.mbnmr.R

CoxBcv.mbnmrR Documentation

Hybrid MBNMR bias-corrected sandwich variance estimator

Description

Calculate the hybrid MBNMR bias-corrected sandwich variance estimator for marginal Cox analysis of cluster randomized trials, proposed by Wang et al. (under review). MBN: Morel, Bokossa, and Neerchal (2003); MR: martingale residual.

Usage

CoxBcv.mbnmr(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.

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

References

Morel, J. G., Bokossa, M. C., & Neerchal, N. K. (2003). Small sample correction for the variance of GEE estimators. Biometrical Journal: journal of mathematical methods in biosciences, 45(4), 395-409.

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.mbnmr(Y,Delta,X,ID)

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


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