Mixed Models

Ludwig Fahrmeir, Thomas Kneib, Stefan Lang and Brian Marx
Additional contact information
Ludwig Fahrmeir: University of Munich, Department of Statistics
Thomas Kneib: University of Göttingen, Chair of Statistics
Stefan Lang: University of Innsbruck, Department of Statistics
Brian Marx: Louisiana State University, Experimental Statistics

Chapter 7 in Regression, 2013, pp 349-412 from Springer

Abstract: Abstract Mixed models extend the predictor $$\eta \,=\,\boldsymbol{x}\prime\boldsymbol{\beta }$$ of linear, generalized linear, and categorical regression models by incorporating random effects or coefficients in addition to the non-random or “fixed” effects $$\boldsymbol{\beta }$$ . Therefore, mixed models are sometimes also called random effects models, and have become quite popular for analyzing longitudinal data obtained from repeated observations on individuals or objects in longitudinal studies. A closely related situation is the analysis of clustered data, i.e., when observations are obtained from objects selected by subsampling primary sampling units (clusters or groups of objects) in cross-sectional studies. For example, clusters may be defined by hospitals, schools, or firms, where data from (possibly small) subsamples of patients, students, or clients are collected.

Keywords: Bayesian Inference; Random Slope; Random Intercept; Marginal Model; Store Brand (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-34333-9_7

Ordering information: This item can be ordered from
http://www.springer.com/9783642343339

DOI: 10.1007/978-3-642-34333-9_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().