varest function

Variance estimate with sandwich formula based on the ES algorithm

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

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.