A BAYESIAN ANALYSIS OF REGRESSION MODELS WITH CONTINUOUS ERRORS WITH APPLICATION TO LONGITUDINAL STUDIES

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...

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Bibliographic Details
Published in:Statistics in medicine 1997-02, Vol.16 (4), p.321-332
Main Authors: BROEMELING, LYLE D., COOK, PEYTON
Format: Article
Language:English
Subjects:
Bayes Theorem
Biological and medical sciences
Cephalometry
Computerized, statistical medical data processing and models in biomedicine
Fetus - anatomy & histology
Humans
Likelihood Functions
Longitudinal Studies
Medical sciences
Medical statistics
Models, Statistical
Regression Analysis
Sample Size
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Summary: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. © 1997 by John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/(SICI)1097-0258(19970228)16:4<321::AID-SIM418>3.0.CO;2-1