Behavior Modification

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

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
Right arrow Citation Map
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 Similar articles in PubMed
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 Parker, R. I.
Right arrow Articles by Hagan-Burke, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Parker, R. I.
Right arrow Articles by Hagan-Burke, S.
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?
Behavior Modification, Vol. 31, No. 6, 919-936 (2007)
DOI: 10.1177/0145445507303452

Median-Based Overlap Analysis for Single Case Data

A Second Study

Richard I. Parker

Texas A&M University, College Station

Shanna Hagan-Burke

Texas A&M University, College Station

This article takes a further look at the percentage of data points exceeding the median (PEM) analysis method for single-case research data, first presented in this journal by Hsen-Hsing Ma. Ma examined the relationship between PEM and the established percentage of nonoverlapping data (PND) and then applied PEM in a meta-analysis of 61 data sets, correlating their authors' judgments of intervention effectiveness with PEM. The present article covers PEM's historical and statistical context and then applies the new measure in a field test with 165 contrasts between a baseline phase A and a treatment phase B. For comparison, Pearson r , Kruskal-Wallis W, PND, and IRD (improvement rate difference) indices also are calculated and correlated with PEM, and all distributions are examined. Expert visual analysis ratings of the 165 graphs are correlated with all indices. PEM surpassed PND in its validation by other established measures. However, PEM was weaker in distribution shape and visual judgment validation. More strongly validated than either PEM or PND was the new nonparametric measure, IRD.

Key Words: single case research methods • effect sizes • single case data analysis


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?