Which is the best two-level hierarchical linear model?

Which is the best two-level hierarchical linear model?

This document serves to compare the procedures and output for two-level hierarchical linear models from six different statistical software programs: SAS, Stata, HLM, R, SPSS, and Mplus. We compare these packages using the popular.csvdataset from Chapter 2 of Joop Hox’s

What is the syntax for a hierarchical model?

The code/syntax used for each model is included below for all programs except HLM, which is completely run by a GUI. We have provided screen shots of HLM and SPSS for each model. In addition, each model is specified in a hierarchical format as well as a mixed format.

Which is a special case of a multilevel model?

Multilevel Analysis(2010), which can be downloaded from: http://joophox.net/mlbook2/DataExchange.zip The six models described below are all variations of a two-level hierarchical model, also referred to as a multilevel model, a special case of mixed model.

Can a HLM be used for crossed designs?

Although the website for the HLM software states that it can be used for crossed designs, this has not been confirmed. The procedures used in SAS, Stata, R, SPSS, and Mplus below are part of their multilevel or mixed model procedures, and can be expanded to non-nested data.

When to use hierarchical linear regression in OLS?

Hierarchical Linear Modeling (HLM) is a complex form of ordinary least squares (OLS) regression that is used to analyze variance in the outcome variables when the predictor variables are at varying hierarchical levels; for example, students in a classroom share variance according to their common teacher and common classroom.

How is the ICC calculated in a hierarchical model?

The ICC is the proportion of variance in the outcome variable that is explained by the grouping structure of the hierarchical model. It is calculated as a ratio of group-level error variance over the total error variance: , where