EM algorithm is based on Peng et al. (2007) and ES algorithm is based on Niu and Peng (2013). ES algorithm is an estension of the EM algorithm where the M-step of the EM algorithm is replaced by a step requiring the solution of a series of generalised estimating equations. Both algorithm are used for the analysis of survival cure data with potential correlation.
1 | emes(Time, Status, X, Z, id, corstr, stdz, esmax, eps)
|
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 |
corstr |
a character string specifying the correlation structure. The following are permitted: |
stdz |
If it is TRUE, all the covariates in the |
esmax |
specifies the maximum iteration number. If the convergence criterion is not met, the ES iteration will be stopped after |
eps |
tolerance for convergence. The default is |
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