dot-test: Single-split test

In rauschenberger/cornet: Penalised Regression for Dichotomised Outcomes

Single-split test

Description

Compares models for a continuous response with a cut-off value.

Usage

.test(y, cutoff, X, alpha = 1, type.measure = "deviance")

Arguments

y	continuous outcome: vector of length n
cutoff	cut-off point for dichotomising outcome into classes: meaningful value between min(y) and max(y)
X	features: numeric matrix with n rows (samples) and p columns (variables)
alpha	elastic net mixing parameter: numeric between 0 (ridge) and 1 (lasso)
type.measure	loss function for binary classification: character "deviance", "mse", "mae", or "class" (see cv.glmnet)

Details

Splits samples into 80 percent for training and 20 percent for testing, calculates squared deviance residuals of logistic and combined regression, conducts the paired one-sided Wilcoxon signed rank test, and returns the p-value. For the multi-split test, use the median p-value from 50 single-split tests (van de Wiel 2009).

Examples

n <- 100; p <- 200
y <- rnorm(n)
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
cornet:::.test(y=y,cutoff=0,X=X)

rauschenberger/cornet documentation built on Sept. 29, 2024, 3:08 a.m.