Bayesian Item Calibration
Bayesian Item Calibration is a statistical method for estimating item parameters in item response theory that incorporates prior distributions to update parameter estimates through Bayesian inference.
16
Publications
768
Citations
27
Authors
14
Institutions
Publications per year
2017–2026
3
Parents
16
Hariharan Swaminathan, Ronald K. Hambleton, Stephen G. Sireci et al. · Applied Psychological Measurement · 2003 · 51 citations · Full text
1–5 of 16
27
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1–5 of 27
14
Educational Testing Service
Princeton, United States
4 h-index
6 publications
182 citations
Baruch College
New York, United States
4 h-index
4 publications
115 citations

University of Twente
Enschede, The Netherlands
3 h-index
5 publications
450 citations
German Institute for Adult Education – Leibniz Centre for Lifelong Learning
Bonn, Germany
1 h-index
1 publications
24 citations

Beijing Normal University
Beijing, China
1 h-index
1 publications
18 citations

University of Oslo
Oslo, Norway
1 h-index
1 publications
24 citations
Goethe University Frankfurt
Frankfurt am Main, Germany
1 h-index
2 publications
48 citations

California State University, Monterey Bay
Seaside, United States
1 h-index
1 publications
40 citations
1–8 of 14
7 publications · 273 citations
7
h-index
2 publications · 74 citations
2
h-index
2 publications · 210 citations
2
h-index
2 publications · 36 citations
2
h-index
EM · 1 publications · 45 citations
1
h-index
1–5