cv.seqlr.batting {SubgrpID}

cv.seqlr.batting

Description

Cross Validation for Sequential BATTing

Usage

cv.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,
  k.fold = 5,
  cv.iter = 50,
  max.iter = 500
)

Arguments

y

data frame containing the response

x

data frame containing the predictors

censor.vec

vector giving 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.

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).

Details

Cross Validation for Sequential BATTing

Value

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