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Correlated datasets arise from repeated measures studies where multiple observations are collected from a specific sampling unit (a specific patient's status over time), or from grouped or clustered data where observations are grouped based on sharing some common characteristic (animals in a specific litter). When measurements are collected over time, the term longitudinal or panel data is preferred. Generalized estimating equations provide a framework for analyzing correlated data. This framework extends the generalized linear models methodology, which assumes independent data. We discuss the estimation of model parameters and associated variances via generalized estimating equation methodology. Generalized Linear Models The theory and an algorithm appropriate for obtaining maximum likelihood estimates where the response follows a distribution in the exponential family (see Generalized Linear Models: Introduction) was introduced in . This reference introduced the term generalized linear models (GLMs) to refer to a class

Author

James W. Hardin

Publisher

Wiley

Published

2014

Language

EN