Evaluating distributional regression strategies for modelling self-reported sexual age-mixing.
age mixing
bayesian statistics
distributional regression
epidemiology
global health
none
sexual behaviour
sinh-arcsinh distribution
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
24 06 2021
24 06 2021
Historique:
received:
11
03
2021
accepted:
23
06
2021
pubmed:
25
6
2021
medline:
9
10
2021
entrez:
24
6
2021
Statut:
epublish
Résumé
The age dynamics of sexual partnership formation determine patterns of sexually transmitted disease transmission and have long been a focus of researchers studying human immunodeficiency virus. Data on self-reported sexual partner age distributions are available from a variety of sources. We sought to explore statistical models that accurately predict the distribution of sexual partner ages over age and sex. We identified which probability distributions and outcome specifications best captured variation in partner age and quantified the benefits of modelling these data using distributional regression. We found that distributional regression with a sinh-arcsinh distribution replicated observed partner age distributions most accurately across three geographically diverse data sets. This framework can be extended with well-known hierarchical modelling tools and can help improve estimates of sexual age-mixing dynamics.
Identifiants
pubmed: 34165078
doi: 10.7554/eLife.68318
pii: 68318
pmc: PMC8263061
doi:
pii:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Bill and Melinda Gates Foundation
ID : OPP1164897
Organisme : Engineering and Physical Sciences Research Council
ID : EP/V002910/1
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : NIAID NIH HHS
ID : R01 AI136664
Pays : United States
Organisme : Bill and Melinda Gates Foundation
ID : OPP1190661
Informations de copyright
© 2021, Wolock et al.
Déclaration de conflit d'intérêts
TW, SF, KR, TD, SG, JE No competing interests declared
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