A general class of hierarchical ordinal regression models with applications to correlated roc analysis

DOI10.2307/3315913zbMath0966.62046OpenAlexW1990449216MaRDI QIDQ2714923

Constantine A. Gatsonis, Hemant Ishwaran

Publication date: 26 July 2001

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/4527d9a5e082283729d21001b16e6e6cb4f9bcf7

zbMATH Keywords

Gibbs samplingROC curveBayesian hierarchical modelordinal regressionMRIordinal categorical dataHROC model

Mathematics Subject Classification ID

Multivariate analysis (62H99) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Linear inference, regression (62J99) Parametric inference (62F99) Biomedical imaging and signal processing (92C55)

Related Items (8)

Bayesian model choice in cumulative link ordinal regression models ⋮ The analysis of ordered categorical data: An overview and a survey of recent developments. (With discussion) ⋮ Modeling Clustered Ordered Categorical Data: A Survey ⋮ A clipped latent variable model for spatially correlated ordered categorical data ⋮ Univariate and multirater ordinal cumulative link regression with covariate specific cutpoints ⋮ Exact Bootstrap Variances of the Area Under ROC Curve ⋮ Random Effects Modeling Approaches for Estimating ROC Curves from Repeated Ordinal Tests without a Gold Standard ⋮ Tree-structured scale effects in binary and ordinal regression

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