Model Diagnostics for Bayesian Networks  

Oleh:

Sinharay, Sandip

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Journal Of Educational And Behavioral Statistics vol. 31 no. 1 (2006), page 1-34.
Topik: discrepancy measure; Mantel–Haenszel statistic; p-values; posterior predictive model checking
Fulltext: 1.pdf (2.5MB)

Isi artikel

Bayesian networks are frequently used in educational assessments primarily for learning about students’ knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A number of aspects of model fit, those of usual interest to practitioners, are assessed using various diagnostic tools. This article suggests a direct data display for assessing overall fit, suggests several diagnostics for assessing item fit, suggests a graphical approach to examine if the model can explain the association among the items, and suggests a version of the Mantel– Haenszel statistic for assessing differential item functioning. Limited simulation studies and a real data application demonstrate the effectiveness of the suggested model diagnostics.

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