Predicting stillbirth using LASSO with structured penalties
Access Status
Open access
Authors
Whitney, Emily
Phatak, Aloke
Pereira, Gavin
Date
2019Type
Conference Paper
Metadata
Show full item recordCitation
Whitney, E. and Phatak, A. and Pereira, G. 2019. Predicting stillbirth using LASSO with structured penalties. In Proceedings of the 34th International Workshop on Statistical Modelling. 7-12 July 2019, Guimarães, Portugal.
Source Title
Proceedings of the 34th International Workshop on Statistical Modelling, Volume II
Source Conference
International Workshop on Statistical Modelling
ISBN
Faculty
Faculty of Science and Engineering
School
Curtin Institute for Computation (CiC)
Collection
Abstract
Using a structured fusion penalty in regression models containing only categorical explanatory variables yields patterns of indicator variables that are simpler and more easily interpretable than regressions produced using the more commonly-used LASSO and group LASSO penalties. We construct logistic regression models for predicting stillbirth from categorical explanatory variables and demonstrate that using a structured fusion penalty produces regressions that are easier to interpret yet yield similar predictive ability.