Linear and Generalized Linear Mixed Models and Their Applications
- Author
- Jiming Jiang, Thuan Nguyen
- Publication Year
- 2021
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Computer Science
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This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics.
Keywords: Mathematics and Statistics / Statistics for Life Sciences, Medicine, Health Sciences / Probability Theory and Stochastic Processes / Statistical Theory and Methods / Numerical Analysis / Genetics and Population Dynamics / Regression analysis / Data analysis / Generalized linear mixed models / Linear mixed models / Linear optimization / Mathematical statistics / Model selection / Random effects / Public health / Mixed model prediction / Restricted maximum likelihood / Small area estimation / Variance components
