• Summary
  • Contents
  • Subject index

In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling.

The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field.

Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference; Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models; Part III includes discussion of missing data and robust methods, assessment of fit and ...

Generalized Linear Mixed Models: Estimation and Inference
Generalized linear mixed models: Estimation and inference
CharlesE.McCulloch and JohnM.NeuhausUniversity of California, San Francisco, USA
15.1 Introduction

Statistical investigations often focus on the analysis of responses gathered in clusters or measured in longitudinal studies. For example, the OAI study (http://www.oai.ucsf.edu) enrolled approximately 5,000 participants and assessed them yearly for osteoarthritis, a degenerative joint disease, which is the major cause of physical disability in older persons. It is characterized by pain, stiffness, and loss of cartilage (a tissue that creates a cushion between bones in joints). The OAI obtained clinical information as well as X-rays and magnetic resonance images (MRIs) of both knees (the most common location of osteoarthritis). Consider studying the outcome of severe pain in a knee with a predictor ...

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