Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

Vol. 3 No. 1

Year: 2009

Issue: May-July

Title: Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis 

Author Name: Brandon K. Vaughn, Dr. Qiu Wang 

Synopsis: 

Many areas in educational and psychological research involve the use of classification statistical analysis.  For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts.  In psychology, a researcher might be interested in the classification of a subject into a particular psychological construct.  The purpose of this study is to investigate alternative procedures to classification other than the use of discriminant and logistic regression analysis.  A classification rule utilizing hierarchical linear modeling (HLM) will be derived and examined, with a following example which will show the benefit for using such an approach by comparing the hit rates to those of a logistic regression analysis.