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R-Squared Measures for Two-Level Hierarchical Linear Models UsingSAS
2010
Journal of Statistical Software
The hierarchical linear model (HLM) is the primary tool of multilevel analysis, a set of techniques for examining data with nested sources of variability. The concept of R 2 from classical multiple regression analysis cannot be applied directly to HLMs without certain undesirable results. However, multilevel analogues have been formulated. The goal here is to demonstrate a SAS macro that will calculate estimates of these quantities for a two-level HLM that has been fit with SAS's linear mixed modeling procedure, PROC MIXED.
doi:10.18637/jss.v032.c02
fatcat:a2vgub3eqbfp7dbeuwy2rexale