Geodesic
Application of HLM to data with multilevel structure
Discussiones Mathematicae. Probability and Statistics, Tome 31 (2011) no. 1-2, pp. 87-101.

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Many data sets analyzed in human and social sciences have a multilevel or hierarchical structure. By hierarchy we mean that units of a certain level (also referred micro units) are grouped into, or nested within, higher level (or macro) units. In these cases, the units within a cluster tend to be more different than units from other clusters, i.e., they are correlated. Thus, unlike in the classical setting where there exists a single source of variation between observational units, the heterogeneity between clusters introduces an additional source of variation and complicates the analysis.
Keywords: hierarchical linear model, multilevel model, cross-classification models, academic achievement 
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Valente, Vítor; Oliveira, Teresa. Application of HLM to data with multilevel structure. Discussiones Mathematicae. Probability and Statistics, Tome 31 (2011) no. 1-2, pp. 87-101. http://geodesic.mathdoc.fr/item/DMPS_2011_31_1-2_a6/

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