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Autoregressive models for describing non‐linear changes in biological parameters fitted using BUGS
Author(s) -
Mander A. P.,
Hughes M. D.,
Sharp S. J.,
Lamm C. J.
Publication year - 1999
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19991030)18:20<2709::aid-sim236>3.0.co;2-g
Subject(s) - autoregressive model , computer science , linear model , statistics , econometrics , mathematics
Many biological processes give outcome data which show a curvilinear association with time which tends to an asymptote. We show how autoregressive models can be used to describe this association within individual subjects. We also present a Bayesian approach implemented using statistical software, BUGS, to fit these models in a multi‐level (hierarchical) setting that describes variation in the association between subjects. Peak expiratory flow data from a clinical trial involving subjects with asthma are used to illustrate the methods. Copyright © 1999 John Wiley & Sons, Ltd.