Document Detail

Analysis of longitudinal count data with serial correlation.
MedLine Citation:
PMID:  17623346     Owner:  NLM     Status:  MEDLINE    
We propose a state space model for analyzing equally or unequally spaced longitudinal count data with serial correlation. With a log link function, the mean of the Poisson response variable is a nonlinear function of the fixed and random effects. The random effects are assumed to be generated from a Gaussian first order autoregression (AR(1)). In this case, the mean of the observations has a log normal distribution. We use a combination of linear and nonlinear methods to take advantage of the Gaussian process embedded in a nonlinear function. The state space model uses a modified Kalman filter recursion to estimate the mean and variance of the AR(1) random error given the previous observations. The marginal likelihood is approximated by numerically integrating out the AR(1) random error. Simulation studies with different sets of parameters show that the state space model performs well. The model is applied to Epileptic Seizure data and Primary Care Visits Data. Missing and unequally spaced observations are handled naturally with this model.
Stanley Xu; Richard H Jones; Gary K Grunwald
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Biometrical journal. Biometrische Zeitschrift     Volume:  49     ISSN:  0323-3847     ISO Abbreviation:  Biom J     Publication Date:  2007 Jun 
Date Detail:
Created Date:  2007-07-17     Completed Date:  2007-08-17     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  7708048     Medline TA:  Biom J     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  416-28     Citation Subset:  IM    
Kaiser Permanente Colorado, P.O. Box 378066, Denver, Colorado 80237, USA.
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MeSH Terms
Clinical Trials as Topic / statistics & numerical data*
Data Interpretation, Statistical
Longitudinal Studies
Models, Statistical*
Normal Distribution
Public Health Informatics

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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