A lean additive frailty model: With an application to clustering of melanoma in Norwegian families.
computational complexity
correlated survival data
frailty
melanoma
susceptibility
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
15 10 2023
15 10 2023
Historique:
revised:
25
06
2023
received:
14
11
2022
accepted:
09
07
2023
medline:
19
9
2023
pubmed:
2
8
2023
entrez:
1
8
2023
Statut:
ppublish
Résumé
Additive frailty models are used to model correlated survival data. However, the complexity of the models increases with cluster size to the extent that practical usage becomes increasingly challenging. We present a modification of the additive genetic gamma frailty (AGGF) model, the lean AGGF (L-AGGF) model, which alleviates some of these challenges by using a leaner additive decomposition of the frailty. The performances of the models were compared and evaluated in a simulation study. The L-AGGF model was used to analyze population-wide data on clustering of melanoma in 2 391 125 two-generational Norwegian families, 1960-2015. Using this model, we could analyze the complete data set, while the original model limited the analysis to a restricted data set (with cluster sizes
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4207-4235Informations de copyright
© 2023 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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