elastic.net: Main Elastic Net Wrapper Function

In pranavdorbala/proteomicsHF: ARIC Proteomics of Heart Failure -- Biomarker Discovery Pipeline

Description

This function is a wrapper function to the glmnet::cv.glmnet() function to conduct LASSO / ElasticNet regularized regression. The regression optimizes the C statistic, forces the adjustment variables, and runs the algorithm using parallel processing.

Usage

elastic.net(data, terms, adjust, time, outc, .alpha = 1)

Arguments

data	The tibble containing the merged Protein and Study Data.
terms	The terms to consider in the LASSO Regression.
adjust	The vector of Adjustment variables to force
time	A character vector of the Survival time to event outcome variable.
outc	A character vector of the Survival event indicator outcome variable.
.alpha	The optional alpha parameter to change LASSO to Elastic Net.

Value

model

The returned cv.glmnet LASSO Elastic Net Model.

coefs

The coefficients of the Non-zero covariates retained.

terms

The Final retained Proteins from this model.

Examples

## Not run: 

 fifth.lasso <- elastic.net(fifth.visit,
                            bonferroni$kept,
                            adjust, time, outc)


## End(Not run)

pranavdorbala/proteomicsHF documentation built on March 9, 2021, 12:22 a.m.