Using Machine Learning to Identify and Investigate Moderators of Alcohol Use Intervention Effects in Meta-Analyses | Zendy

Nicholas J. Parr | Zendy; Christopher M. Loan | Zendy; Emily E. TannerSmith | Zendy

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Using 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.

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