seqlr.batting: Perform sequential BATTing method.

In SubgrpID: Patient Subgroup Identification for Clinical Drug Development

Description

Perform sequential BATTing method.

Usage

seqlr.batting(y, x, censor.vec = NULL, trt.vec = NULL, trtref = NULL,
  type = "c", n.boot = 50, des.res = "larger", class.wt = c(1, 1),
  min.sigp.prcnt = 0.2, pre.filter = NULL, filter.method = NULL)

Arguments

y	data frame containing the response.
x	data frame containing the predictors.
censor.vec	vector containing the censor status (only for TTE data , censor=0,event=1) - default = NULL.
trt.vec	vector containing values of treatment variable ( for predictive signature). Set trt.vec to NULL for prognostic signature.
trtref	code for treatment arm.
type	data type. "c" - continuous , "b" - binary, "s" - time to event : default = "c".
n.boot	number of bootstraps in BATTing step.
des.res	the desired response. "larger": prefer larger response. "smaller": prefer smaller response
class.wt	vector of length 2 used to weight the accuracy score , useful when there is class imbalance in binary data defaults to c(1,1)
min.sigp.prcnt	desired proportion of signature positive group size for a given cutoff.
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

it returns a list of signature rules consisting of variable names, directions, thresholds and the loglikelihood at each step the signatures are applied.

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