Robust Mixture Priors
Robust Mixture Priors is a Bayesian prior modeling approach that belongs to the class of hierarchical priors and is specifically characterized by its construction as a finite mixture of competing prior distributions to ensure inferential stability and insensitivity to prior misspecification in clinical trial settings.
8
Publications
725
Citations
24
Authors
20
Institutions
Publications per year
2017–2026
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Parents
8
1–5 of 8
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Novartis (Switzerland)
Basel, Switzerland
3 h-index
4 publications
982 citations
University of Cambridge
Cambridge, United Kingdom
1 h-index
1 publications
466 citations
University of Sheffield
Sheffield, United Kingdom
1 h-index
1 publications
466 citations

Statistics Belgium
Brussels, Belgium
1 h-index
1 publications
28 citations
German Cancer Research Center
Heidelberg, Germany
1 h-index
2 publications
78 citations
KU Leuven
Leuven, Belgium
1 h-index
1 publications
28 citations
Roche (Switzerland)
Basel, Switzerland
1 h-index
2 publications
56 citations
GlaxoSmithKline (Sri Lanka)
Moratuwa, Sri Lanka
1 h-index
3 publications
108 citations
1–8 of 20
2 publications · 64 citations
2
h-index
2 publications · 505 citations
2
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1 publications · 87 citations
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1 publications · 19 citations
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1 publications · 10 citations
1
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1–5