Open AccessUsing Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse
Author(s) -
Robert Suchting,
Emily T. Hébert,
Ping Ma,
Darla E. Kendzor,
Michael S. Businelle
Publication year - 2017
Publication title -
nicotine and tobacco research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.338
H-Index - 113
eISSN - 1469-994X
pISSN - 1462-2203
DOI - 10.1093/ntr/ntx201
Subject(s) - elastic net regularization , generalizability theory , proportional hazards model , psychological intervention , smoking cessation , regression , regression analysis , medicine , psychosocial , statistics , mathematics , psychiatry , pathology
Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological momentary assessment (EMA). Understanding these predictors may aid in developing interventions for smoking lapse prevention.