f.learn.1: Learning Stage Analyses on a Single Dataset

In gu-mi/simASD: Enhancement of the Adaptive Signature Design (ASD) for Learning and Confirming in a Single Pivotal Trial

Description

This function analyzes a single dataset and prepares quantities for the subsequent confirm stage analysis.

Usage

f.learn.1(data.1, learn.allocation = 30, cutoff = 0.4, side = "LT")

Arguments

data.1	an individual dataset consisting of all variables needed in an ASD
learn.allocation	percentage of all subjects allocated to the learn stage: specify 30 means 30% of subjects are allocated to the learn stage, while 70% of subjects to the confirm stage
cutoff	biomarker cutoff value for learn-stage dataset: a numerical value
side	how to define sensitive subgroup using the cutoff value. Default is "LT" (less than), indicating subjects in the subgroup all have biomarker value < cutoff. Alternatively, "GT" (greater than), "LE" (less or equal to) or "GE" (greater or equal to) can be specified.

Value

a list of intermediate data results to be used for subsequent confirm stage analysis

Author(s)

Gu Mi <[e-mail]>

See Also

f.confirm.1 for confirm stage analysis for a single dataset f.learn.confirm for the main function of learn/confirm analysis

gu-mi/simASD documentation built on May 17, 2019, 8:57 a.m.