Bayesian Inference on Changes in Response Densities over Predictor Clusters

Journal of the American Statistical Association
David B DunsonAnna Maria Siega-Riz

Abstract

In epidemiology, it is often of interest to assess how individuals with different trajectories over time in an environmental exposure or biomarker differ with respect to a continuous response. For ease in interpretation and presentation of results, epidemiologists typically categorize predictors prior to analysis. To extend this approach to time-varying predictors, one can cluster individuals by their predictor trajectory, with the cluster index included as a predictor in a regression model for the response. This article develops a semiparametric Bayes approach, which avoids assuming a pre-specified number of clusters and allows the response to vary nonparametrically over predictor clusters. This methodology is motivated by interest in relating trajectories in weight gain during pregnancy to the distribution of birth weight adjusted for gestational age at delivery. In this setting, the proposed approach allows the tails of the birth weight density to vary flexibly over weight gain clusters.

References

Feb 13, 1999·Paediatric and Perinatal Epidemiology·D A SavitzB Eucker

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Citations

Mar 13, 2015·Biometrics·Luke B SmithMontserrat Fuentes
May 10, 2017·International Journal of Environmental Research and Public Health·Eric CokerBrenda Eskenazi
Jan 18, 2018·PLoS Computational Biology·Ian C McDowellBarbara E Engelhardt
Jul 1, 2014·Journal of the American Statistical Association·Bruno Scarpa, David B Dunson
Dec 12, 2018·Statistical Methods in Medical Research·Zihang Lu, Wendy Lou
Jan 19, 2018·Paediatric and Perinatal Epidemiology·Jennifer A Hutcheon, Lisa M Bodnar
Apr 10, 2009·Biometrical Journal. Biometrische Zeitschrift·David B Dunson
Feb 11, 2018·Current Environmental Health Reports·Eric CokerJohn Molitor
Nov 3, 2010·Biometrics·Joyee GhoshAnna Maria Siega-Riz
Oct 12, 2020·Statistics in Medicine·Nicolò MargaritellaRuth King
Sep 26, 2021·Biometrics·Glen McGeeBrent A Coull

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