Bayesian Log-linear Models
Bayesian Log-Linear Models is a statistical modeling framework that extends classical log-linear models by incorporating Bayesian inference, wherein prior distributions are assigned to model parameters and posterior distributions are derived to estimate associations in contingency table data while accounting for uncertainty.
46
Publications
2.1K
Citations
148
Authors
99
Institutions
Publications per year
2017–2026
13
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46
1–5 of 46
148
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Centers for Disease Control and Prevention, United States
3 publications · 109 citations
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2
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1–5 of 148
99

University of St Andrews
St Andrews, United Kingdom
4 h-index
6 publications
192 citations
Bowling Green State University
Bowling Green, United States
3 h-index
3 publications
102 citations

Centers for Disease Control and Prevention
Atlanta, United States
3 h-index
5 publications
148 citations

Hankuk University of Foreign Studies
Seoul, South Korea
3 h-index
3 publications
119 citations
University of Michigan
Ann Arbor, United States
3 h-index
3 publications
111 citations

University of Warwick
Coventry, United Kingdom
3 h-index
4 publications
94 citations
University of Wisconsin–Madison
Madison, United States
2 h-index
6 publications
252 citations
MRC Biostatistics Unit
Cambridge, United Kingdom
2 h-index
3 publications
205 citations
1–8 of 99
7 publications · 266 citations
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2 publications · 70 citations
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2 publications · 77 citations
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2 publications · 83 citations
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2 publications · 34 citations
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