Multilevel modelling glossary
- Cluster: A grouping containing lower level elements. For example in a sample survey the set of households in a neighbourhood.
- Cross classification: A structure where lower level units are grouped within the cells of a multiway classification of higher level units
- Design matrix: In the fixed part of the model, the matrix of values of the explanatory variables X. In the random part the matrix of explanatory variables Z.
- Explanatory variable: Also known as an ‘independent’ variable. In the fixedpart of the model usually denoted by X and in the random part by Z.
- Fixed part:That part of a model represented by Xß, that is the average relationship.
- Level:A component of a data hierarchy. Level 1 is the lowest level, for example students within schools or repeated measurement occasions within individual subjects.
- Level n variation: The variation among level n unit measurements.
- Multiple membership: A structure where a level unit may be nested within one or more higher level units.
- Nesting:The clustering of units into a hierarchy
- Random part:That part of a model represented by Zu, that is the contribution of the random variables, at each level.
- Response variable:Also known as a ‘dependent’ variable. Denoted by y.
- Unit:An entity defined at a level of a data hierarchy. For example an individual student will be a level 1 unit within a level 2 unit such as a school.
The above terms are courtesy of: Goldstein, H. (2003). Multilevel Statistical Models (3rd Edition). London, Edward Arnold: New York, Halstead Press.