prim.train: The main PRIM function

In SubgrpID: Patient Subgroup Identification for Clinical Drug Development

Description

The main PRIM function

Usage

prim.train(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)

Arguments

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

Value

the final list of rules selected by PRIM.

SubgrpID documentation built on May 2, 2019, 8:02 a.m.