varest {geecure}

Variance estimate with sandwich formula based on the ES algorithm

Description

Calculate the variance estimates using the sandwich formula based on the ES algorithm.

Usage

varest(Time, Status, X, Z, id, gamma, beta, kappa, gphi, gcor, bphi, bcor, 
       Lambda, w, model)

Arguments

Time

right censored data which is the follow up time.

Status

the censoring indicator, normally 0 = event of interest happens, and 0 = censoring.

X

a matrix of covariates corresponding to the latency part.

Z

a matrix of covariates corresponding to the incidence part.

id

a vector which identifies the clusters. The length of id should be the same as the number of observations.

gamma

the estimates for the incidence part.

beta

the estimates for the latency part.

kappa

the estimate of the shape parameter in the Weibull baseline hazard function when model = "para".

gphi

the estimate of the scale parameter \phi_1 in the GEE for the incidence part.

gcor

the estimate of the correlation parameter \rho_1 in the GEE for the incidence part.

bphi

the estimate of the scale parameter \phi_2 in the GEE for the latency part.

bcor

the estimate of the correlation parameter \rho_2 in the GEE for the latency part.

Lambda

the estimate of the cumulative baseline hazard function in the GEE for the latency part.

w

conditional probability of a patient remains uncured.

model

specifies your model, it can be para which represents the parametric PHMC model with two-parameter Weibull baseline survival function, or semi which represents the semiparametric PHMC model.