README.md

In bips-hb/batchlasso: BatchLASSO

batchLASSO for more easily performing ROC and PRC analysis with the LASSO

batchLASSO is a minimalistic R package for creating ROCs and PRCs when applying the LASSO on binary data with multiple responses and multiple covariates (exposures).

batchlasso can be used to rank the response-exposure pairs from most to least 'interesting'. Simply using the resulting regression coefficients would be unwise, since the size of the coefficients cannot be compared from model to model. Instead, we use the tuning parameter, lambda.

Each response variable in the given response matrix is regressed on all exposures in the matrix exposure. We determine for each exposure what the highest value of lambda for which that variable is included for the first time in the regression model (i.e., its regression coefficient is non-zero). These lambda-values can be compared across models.

See for the details ?batchLASSO.

Acknowledgements

We gratefully acknowledge the financial support from the innovation fund (“Innovationsfonds”) of the Federal Joint Committee in Germany (grant number: 01VSF16020).

Contact

Louis Dijkstra\ Leibniz Institute for Prevention Research & Epidemiology E-mail: dijkstra (at) leibniz-bips.de

bips-hb/batchlasso documentation built on Dec. 8, 2020, 2 p.m.