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A Bayesian analysis of regression models with continuous errors with application to longitudinal studies.

L D Broemeling·P Cook
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Abstract

We employ a regression model with errors that follow a continuous autoregressive process to analyse longitudinal studies. In this way, unequally spaced observations do not present a problem in the analysis. We employ a Bayesian approach, where our inferences are based on a direct resampling process that generates values from the posterior distribution of the parameters of the model. We illustrate these Bayesian inferences with an analysis of a longitudinal study that involves the regression of foetal head circumference on menstrual age. Using these same data, we contrast the Bayesian approach with a maximum likelihood technique.

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L D Broemeling, P Cook. 1997-02-28. A Bayesian analysis of regression models with continuous errors with application to longitudinal studies.. https://doi.org/10.1002/(sici)1097-0258(19970228)16%3A4%3C321%3A%3Aaid-sim418%3E3.0.co%3B2-1

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