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C McMahan

Datos Biográficos

ID10200119
NOMBREC McMahan
NOMBRESC
APELLIDOMcMahan
FIRMAMCMAHAN C
AFILIACIONESClemson University
VERIFICADONo
TOTAL DE OBRAS1
TOTAL DE CITAS0
OBRAS COMO AUTOR1
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2026
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H0
  • Bayesian Machine Learning Tools for Alcohol Use Disorder Research

    Open Access•James W Baurley, Carolyn M Ervin et al.•ARTICLE•Multivariate Behavioral Research•2026

    Alcohol use disorder (AUD) research faces significant challenges in capturing individual heterogeneity and complex temporal patterns in drinking behaviors. Standard statistical methods fail to account for within-person variability and between-person differences, while existing machine learning algorithms are not designed for hierarchical, longitudinal data structures common in AUD research. We developed a comprehensive R package implementing 30 B…

Sin obras prominentes en esta página.

  • Bayesian Machine Learning Tools for Alcohol Use Disorder Research

    Open Access•James W Baurley, Carolyn M Ervin et al.•ARTICLE•Multivariate Behavioral Research•2026

    Alcohol use disorder (AUD) research faces significant challenges in capturing individual heterogeneity and complex temporal patterns in drinking behaviors. Standard statistical methods fail to account for within-person variability and between-person differences, while existing machine learning algorithms are not designed for hierarchical, longitudinal data structures common in AUD research. We developed a comprehensive R package implementing 30 B…

Alcohol consumption (1 obra) · Alcohol use disorder (1 obra) · Bayesian Methods and Mixture Models (1 obra) · Bayesian network (1 obra) · Bayesian probability (1 obra) · Correlation (1 obra) · Key (lock) (1 obra) · Mental Health Research Topics (1 obra) · Odds (1 obra) · Range (aeronautics) (1 obra)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae