Critical Assumptions and Distribution Features Pertaining to Contemporary Single-Case Effect Sizes

The use of single-case effect sizes (SCESs) has increased in the intervention literature. Meta-analyses based on single-case data have also increased in popularity. However, few researchers who have adopted these metrics have provided an adequate rationale for their selection. We review several impo...

Full description

Saved in:
Bibliographic Details
Published inJournal of behavioral education Vol. 24; no. 4; pp. 438 - 458
Main Authors Solomon, Benjamin G., Howard, Taylor K., Stein, Brit'ny L.
Format Journal Article
LanguageEnglish
Published New York Springer 01.12.2015
Springer US
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN1053-0819
1573-3513
DOI10.1007/s10864-015-9221-4

Cover

Loading…
More Information
Summary:The use of single-case effect sizes (SCESs) has increased in the intervention literature. Meta-analyses based on single-case data have also increased in popularity. However, few researchers who have adopted these metrics have provided an adequate rationale for their selection. We review several important statistical assumptions that should be considered prior to calculating and interpreting SCESs. We then more closely investigate a sampling of these newer procedures and conclude with critical analysis of the potential utility of these metrics.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1053-0819
1573-3513
DOI:10.1007/s10864-015-9221-4