Open AccessUsing Machine Learning to Identify and Investigate Moderators of Alcohol Use Intervention Effects in Meta-Analyses
Author(s) -
Nicholas J. Parr,
Christopher M. Loan,
Emily E. TannerSmith
Publication year - 2021
Publication title -
alcohol and alcoholism
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.747
H-Index - 99
eISSN - 1464-3502
pISSN - 0735-0414
DOI - 10.1093/alcalc/agab036
Subject(s) - moderation , psychological intervention , psychology , intervention (counseling) , meta analysis , clinical psychology , sample size determination , randomized controlled trial , alcohol use disorder , brief intervention , machine learning , alcohol , computer science , medicine , statistics , social psychology , psychiatry , biochemistry , chemistry , mathematics , surgery
To illustrate a machine learning-based approach for identifying and investigating moderators of alcohol use intervention effects in aggregate-data meta-analysis.