Description Usage Arguments Value Author(s) Examples
View source: R/bacisClassification.R
The classification model is conducted based on the BaCIS method and the subgroupos are classified into two clusters: high respone rate cluster and low response rate cluster.
1 2 | bacisClassification(numGroup, tau1, tau2, phi1, phi2,
clusterCutoff, MCNum, nDat, xDat, seed)
|
numGroup |
Number of subgroups in the trial. |
tau1 |
The precision parameter of subgroups clustering for the classification model. |
tau2 |
The precision prior for the latent variable for the classification. |
phi1 |
Center for the low response rate cluster. |
phi2 |
Center for the high response rate cluster. |
clusterCutoff |
The cutoff value of the cluster classification. If its value is NA, adaptive classification is applied. |
MCNum |
The number of MCMC sampling iterations. |
nDat |
The vector of total sample sizes of all subgroups. |
xDat |
The vector of the response numbers of all subgroups. |
seed |
Random seed value. If its value is NA, a time dependent random seed is generated and applied. |
The classification model is applied using the input parameter values and subgroup outcomes. The classification results are returned. The return list includes highResponseGroup and lowResponseGroup index vlaues.
Nan Chen and J. Jack Lee / Department of Biostatistics UT MD Anderson Cancer Center
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