An ensemble mixed effects model of sleep loss and performance

DOI10.1016/J.JTBI.2020.110497zbMath1457.91320OpenAlexW3087581460WikidataQ99614324 ScholiaQ99614324MaRDI QIDQ2225967

Elizabeth B. Klerman, Melissa A. St. Hilaire, Courtney Cochrane, Demba Bocar Ba

Publication date: 11 February 2021

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8631086

zbMATH Keywords

humanmachine learningindividual differencessleep lossensemble mixed effects modelspsychomotor vigilance task

Mathematics Subject Classification ID

Cognitive psychology (91E10) Measurement and performance in psychology (91E45) Biological rhythms and synchronization (92B25)

Uses Software

• lme4
• Python
• GitHub
• Unnamed Item

Cites Work

• A new mathematical model for the homeostatic effects of sleep loss on neurobehavioral performance
• A unified mathematical model to quantify performance impairment for both chronic sleep restriction and total sleep deprivation
• Mixed-effects random forest for clustered data
• Nonparametric Regression Methods for Longitudinal Data Analysis

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