cv_method: Formula-based PCC of a CV-based classifier

In HDDesign: Sample Size Calculation for High Dimensional Classification Study

Description

Determine the probability of correct classification (PCC) for a high dimensional classification study employing cross validation to determine an optimal p-value cutoff to select features that are included in a linear classifier.

Usage

	cv_method(mu0, p, m, n, alpha_list, nrep, p1 = 0.5, ss = F, sampling.p=0.5)

Arguments

mu0	The effect size of the important features.
p	The number of the features in total.
m	The number of the important features.
n	The total sample size for the two groups.
alpha_list	The search grid for the p-value threshold.
nrep	The number of simulation replicates employed to compute the expected PCC and/or sensitivity and specificity.
p1	The prevalence of the group 1 in the population, default to 0.5.
ss	Boolean variable, default to FALSE. The TRUE value instruct the program to compute the sensitivity and the specificity of the classifier.
sampling.p	The assumed proportion of group 1 samples in the training data; default of 0.5 assumes groups are equally represented regardless of p1.

Details

Refer to Sanchez, Wu, Song, Wang 2016, Section 2.2 for the details of the algorithm. This function was used to produce Figure 2 of the paper.

Value

If ss=FALSE, the function returns the expected PCC. If ss=TRUE, the function returns a vector containing the expected PCC, sensitivity and specificity.

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]>

References

Sanchez, B.N., Wu, M., Song, P.X.K., and Wang W. (2016). "Study design in high-dimensional classification analysis." Biostatistics, in press.

Examples

	set.seed(1)
	cv_method(mu0=0.4, p=500, m=10, n=80, alpha_list=c(0.0000001, 0.0001, 0.01), 
	nrep=10, p1=0.6, ss=TRUE)
	#return: 0.8012142 0.8210082 0.7714031
	#alpha_list should be a dense list of p-value cutoffs; 
	#here we only use a few values to ease computation of the example.

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