samplesize: Determine the Sample Size Requirement

In HDDesign: Sample Size Calculation for High Dimensional Classification Study

Description

Determine the sample size to achieve the target probability of correct classification (PCC) using various design methods. Sample sizes are chosen using a binary search algorithm between the range nmin to nmax.

Usage

	samplesize(target, nmin, nmax, f, ...)

Arguments

target	Set the target probability of correct classifcation (PCC) for the study.
nmin	The mimimum sample size for both groups combined. Typically 0.05 smaller than the ideal PCC. It must be an even number.
nmax	The maximum sample size for both groups combined. So it must be an even number.
f	Specify the PCC estimation function: ds_method, cv_method, or hct_method
...	The design assumptions and other arguments for the PCC estimation function, f.

Value

The smallest sample size that achieves the target PCC.

Author(s)

Meihua Wu <[e-mail]> Brisa N. Sanchez <[e-mail]> Peter X.K. Song <[e-mail]> Raymond Luu <[e-mail]> Wen Wang <[e-mail]>

Examples

set.seed(1)
samplesize(target=0.8, nmin=20, nmax=100, hct_method, mu0=0.4, p=500, 
m=10, hct=hct_beta, alpha0=0.5, nrep=100) 
#return: 78.0000000  0.8043205

Example output

[1] 78.0000000  0.8043205

HDDesign documentation built on May 2, 2019, 6:41 a.m.