HLM Examples

To fit models in HLM, 8 statistical applications are used: HLM2, which fits 2-level linear and nonlinear (HGLM) models; HLM3, which fits 3-level linear/nonlinear models; HLM4, which fits 4-level linear/nonlinear models; HMLM, which fits hierarchical multivariate 2-level linear models; HMLM2, which fits hierarchical multivariate 3-level models; HCM2, which fits 2-level crossed-and-nested models, ; HCM3, which fits 3-level crossed-and-nested models; and HLMHCM, which fits linear models with crossed-and-nested random effects. For specific examples for the different modules, please see below.

Two-level models based on the HSB data (download data and command files)

Two-level spatial analysis model (download data and command files)

Three-level models based on the EG data (download data and command files)

Four-level models based on the literacy data (download data and command files)

HGLM models based on the Thai data (download data and command files)

HGLM models based on the Teacher data (download data and command files)

HMLM models based on the NYS data (download data and command files)

HMLM2 model based on the EG data (download data and command files)

HCM2 models based on the Scotland data (download data and command files)

HCM3 model for the Growth data (download data and command files)

HLMHCM models for the Growth data (download data and command files)

Graphing (download data and command files)

Data based graphs:

  • Box-and-whisker plots, which can be used to display univariate distributions of level-1 variables for each level-2 unit, with and without a level-2 classification variable.
  • Line plots, where, for example, level-1 repeated measures observations are joined by lines to describe changes or developments over time during the course of the research study.
  • Scatter plots, which can be used to explore bivariate relationships between level-1 variables for individual or a group of level-2 units, with and without controlling level-2 variables.

Model based graphs

FIRC models (download data and command files)

Augmented imputation models (download data and command files)