Mixed Effects Models for Complex Data

Smith, Richard L. (Series edited by)/ Isham, Valerie (Series edited by)/ Louis, Thomas A. (Series edited by)/ Fan, Jianqing (Series edited by)/ Tong, Howell (Series edited by)/ Keiding, Niels (Series edited by)/ Murphy, Susan.A (Series edited by)/ Wu, Lang (Author)

ISBN 10: 1420074024 / ISBN 13: 9781420074024

Edité par Chapman & Hall, 2009

A propos de cet article

1st edition. 431 pages. 9.57x6.50x1.06 inches. In Stock.

N° de réf. du vendeur x-1420074024

Détails bibliographiques

• Titre: Mixed Effects Models for Complex Data
• Éditeur: Chapman & Hall
• Date de parution: 2009
• Langue: anglais
• ISBN à 10 chiffres: 1420074024
• ISBN à 13 chiffres: 9781420074024
• Reliure: Hardcover
• État de l'article: Brand New

A propos de ce titre

Synopsis

Presenting effective approaches to address missing data, measurement errors, censoring, and outliers in longitudinal data, this book covers linear, nonlinear, generalized linear, nonparametric, and semiparametric mixed effects models. It links each mixed effects model with the corresponding class of regression model for cross-sectional data and discusses computational strategies for likelihood estimations of mixed effects models. The author briefly describes generalized estimating equations methods and Bayesian mixed effects models and explains how to implement standard models using R and S-Plus. The real-world data examples used throughout encompass studies on mental distress, AIDS, and more.

À propos de l?auteur

Lang Wu is an associate professor in the Department of Statistics at the University of British Columbia in Vancouver, Canada.