TY - JOUR TI - Evaluating distributional regression strategies for modelling self-reported sexual age-mixing AU - Wolock, Timothy M AU - Flaxman, Seth AU - Risher, Kathryn A AU - Dadirai, Tawanda AU - Gregson, Simon AU - Eaton, Jeffrey W A2 - Franco, Eduardo A2 - Malagón, Talía A2 - Akullian, Adam VL - 10 PY - 2021 DA - 2021/06/24 SP - e68318 C1 - eLife 2021;10:e68318 DO - 10.7554/eLife.68318 UR - https://doi.org/10.7554/eLife.68318 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. KW - sexual behaviour KW - age mixing KW - bayesian statistics KW - sinh-arcsinh distribution KW - distributional regression JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -