prim.cv: Cross-validation for PRIM
In SubgrpID: Patient Subgroup Identification for Clinical Drug Development

Cross-validation for PRIM

prim.cv(data, yvar, censorvar, trtvar, trtref = NULL, xvars, type, des.res,
  alpha = c(0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5),
  min.sigp.prcnt = 0.2, training.percent = 0.5, n.boot = 0,
  pre.filter = NULL, filter.method = NULL, k.fold = 5, cv.iter = 50,
  max.iter = 500)

`data`	the input data frame
`yvar`	name for response variable
`censorvar`	name for censoring (1: event; 0: censor), default = NULL
`trtvar`	name for treatment variable, default = NULL (prognostic signature)
`trtref`	coding (in the column of trtvar) for treatment arm
`xvars`	vector of variable names for predictors (covariates)
`type`	type of response variable: "c" continuous (default); "s" survival; "b" binary
`des.res`	the desired response. "larger": prefer larger response (default) "smaller": prefer smaller response
`alpha`	a parameter controlling the number of patients in consideration
`min.sigp.prcnt`	desired proportion of signature positive group size for a given cutoff.
`training.percent`	percentage of subjects in the initial training data
`n.boot`	number of bootstrap for the variable selection procedure for PRIM
`pre.filter`	NULL, no prefiltering conducted;"opt", optimized number of predictors selected; An integer: min(opt, integer) of predictors selected
`filter.method`	NULL, no prefiltering, "univariate", univaraite filtering; "glmnet", glmnet filtering, "unicart": univariate rpart filtering for prognostic case
`k.fold`	number of folds for CV.
`cv.iter`	Algorithm terminates after cv.iter successful iterations of cross-validation
`max.iter`	total number of iterations allowed (including unsuccessful ones)

a list containing with following entries:

`stats.summary`	Summary of performance statistics.
`pred.classes`	Data frame containing the predictive clases (TRUE/FALSE) for each iteration.
`folds`	Data frame containing the fold indices (index of the fold for each row) for each iteration.
`sig.list`	List of length cv.iter * k.fold containing the signature generated at each of the k folds, for all iterations.
`error.log`	List of any error messages that are returned at an iteration.
`interplot`	Treatment*subgroup interaction plot for predictive case