Educational and Psychological Measurement

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Register here to gain access to SAGE's 500+ Journals Online

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by DiStefano, C.
Right arrow Articles by Kamphaus, R. W.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Educational and Psychological Measurement, Vol. 66, No. 5, 778-794 (2006)
DOI: 10.1177/0013164405284033

Investigating Subtypes of Child Development

A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

Christine DiStefano

University of South Carolina

R. W. Kamphaus

University of Georgia

Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures and results were compared. The latent class cluster analysis uncovered three classes representing differing levels of children's behavioral adjustment (well adjusted, average adjustment, functionally impaired), whereas the cluster analysis uncovered seven groups of child behavior. Results show a high degree of overlap, and each procedure offers unique information toward classifying child behavior.

Key Words: cluster analysis • latent class cluster analysis • latent profile analysis (LPA) • classification


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?