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Inequality Constrained Multilevel Models

  • Bernet Sekasanvu KatoEmail author
  • Carel F.W. Peeters
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

Abstract

In many areas of research, datasets have a multilevel or hierarchical structure. By hierarchy we mean that units at a certain level are grouped or clustered into, or nested within, higher-level units. The “level” signifies the position of a unit or observation within the hierarchy. This implies that the data are collected in groups or clusters. Examples of clusters are families, schools, and firms. In each of these examples a cluster is a collection of units on which observations can be made. In the case of schools, we can have three levels in the hierarchy with pupils (level 1) within classes (level 2) within schools (level 3). The key thing that defines a variable as being a level is that its units can be regarded as a random sample from a wider population of units.

Keywords

Posterior Distribution Prior Distribution Mathematics Achievement Markov Chain Monte Carlo Method Catholic School 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Twin Research and Genetic Epidemiology UnitSt. Thomas’ Hospital Campus, King’s College LondonLondonUK
  2. 2.Department of Methodology and StatisticsUtrecht UniversityUtrechtthe Netherlands

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