Publications

BibTex format

@article{Wolock:2021:10.7554/eLife.68318,
author = {Wolock, T and Flaxman, S and Risher, K and Dadirai, T and Gregson, S and Eaton, J},
doi = {10.7554/eLife.68318},
journal = {eLife},
pages = {1--38},
title = {Evaluating distributional regression strategies for modelling self-reported sexual age-mixing},
url = {http://dx.doi.org/10.7554/eLife.68318},
volume = {10},
year = {2021}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Wolock,T
AU  - Flaxman,S
AU  - Risher,K
AU  - Dadirai,T
AU  - Gregson,S
AU  - Eaton,J
DO  - 10.7554/eLife.68318
EP  - 38
PY  - 2021///
SN  - 2050-084X
SP  - 1
TI  - Evaluating distributional regression strategies for modelling self-reported sexual age-mixing
T2  - eLife
UR  - http://dx.doi.org/10.7554/eLife.68318
UR  - https://elifesciences.org/articles/68318
UR  - http://hdl.handle.net/10044/1/90631
VL  - 10
ER  -

Download

Jeff Imai-Eaton

Contact

Location

Summary

Citation

BibTex format

RIS format (EndNote, RefMan)