Conditional independence as a statistical assessment of evidence integration processes.
Journal
bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187
Informations de publication
Date de publication:
19 Oct 2023
19 Oct 2023
Historique:
pubmed:
30
8
2023
medline:
30
8
2023
entrez:
30
8
2023
Statut:
epublish
Résumé
Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional independence, we consider expressions that can serve either as recipes for integrating evidence based on limited data, or as statistical benchmarks for characterizing evidence integration processes. Consider three events,
Identifiants
pubmed: 37646001
doi: 10.1101/2023.05.03.539321
pmc: PMC10461915
pii:
doi:
Types de publication
Preprint
Langues
eng
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