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PubMed · 2242408

Some covariance models for longitudinal count data with overdispersion.

P F Thall·S C Vail
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Abstract

A family of covariance models for longitudinal counts with predictive covariates is presented. These models account for overdispersion, heteroscedasticity, and dependence among repeated observations. The approach is a quasi-likelihood regression similar to the formulation given by Liang and Zeger (1986, Biometrika 73, 13-22). Generalized estimating equations for both the covariate parameters and the variance-covariance parameters are presented. Large-sample properties of the parameter estimates are derived. The proposed methods are illustrated by an analysis of epileptic seizure count data arising from a study of progabide as an adjuvant therapy for partial seizures.

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Analysis of VarianceBiometryEpilepsyHumansLongitudinal StudiesModels, StatisticalClinical TrialJournal ArticleRandomized Controlled TrialResearch Support, U.S. Gov't, P.H.S.

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P F Thall, S C Vail. 1990. Some covariance models for longitudinal count data with overdispersion.. https://pubmed.ncbi.nlm.nih.gov/2242408/

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