A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data.

Pan, Tianyu; Shen, Weining; Davis-Stober, Clintin P; Hu, Guanyu

Pan, Tianyu; Shen, Weining; Davis-Stober, Clintin P; Hu, Guanyu.

Afiliação

Pan T; Department of Statistics, University of California, Irvine, California, USA.
Shen W; Department of Statistics, University of California, Irvine, California, USA.
Davis-Stober CP; Department of Psychological Sciences, University of Missouri - Columbia, Columbia, Missouri, USA.
Hu G; Department of Biostatistics and Data Science, Center for Spatial Temporal Modeling for Applications in Population Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, USA.

Br J Math Stat Psychol ; 77(1): 196-211, 2024 Feb.

Article em En | MEDLINE | ID: mdl-37727141

Assuntos

Algoritmos; Estudantes; Humanos; Teorema de Bayes; Análise por Conglomerados

Palavras-chave

IRT model; Rasch model; model averaging; nonparametric Bayesian method; posterior contraction rate

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudantes / Algoritmos Limite: Humans Idioma: En Revista: Br J Math Stat Psychol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

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