Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A New Look at Treatment Differences:

A New Look at Treatment Differences: GARRETT K. MANDEVILLE University of South Carolina Quite frequently in the behavioral sciences, the raw data obtained from an experimental subject are a series of binary responses. In addition to the example of test item data we could include many questionnaire studies and psychological experiments involving discrimi­ nation, perception and the like. If the subjects are also classified on another variable, the design is similar to the split-plot design and is often called a two-factor repeated measures experiment by behavioral researchers. With continuous measurements which fit the normal model the analysis is fairly straightforward. Tests of the assumption of a patterned covariance matrix should be considered but results of Collier, et a/., (1967) indicate that moderate departures do not seriously invalidate the usual tests of significance. For situations in which the researcher feels that this "univariate" approach is unwarranted, a conservative test due to Greenhouse and Geisser (1959) or multivariate procedures described elsewhere e.g., Danford, et aL, (1960); Cole and Grizzle (1966) are appropriate. For dichotomous data, however, the literature provides few clues to aid the researcher. Recent non-parametric results of Koch (1969) which are based on ranks, are not directly applicable for dichotomous data. Other than the use http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Educational Research Journal SAGE

A New Look at Treatment Differences:

Download PDF
11 pages

Loading next page...
 
/lp/sage/a-new-look-at-treatment-differences-75msNfEWQT

References (19)

Publisher
SAGE
Copyright
Copyright © 2019 by American Educational Research Association
ISSN
0002-8312
eISSN
1935-1011
DOI
10.3102/00028312009002311
Publisher site
See Article on Publisher Site

Abstract

GARRETT K. MANDEVILLE University of South Carolina Quite frequently in the behavioral sciences, the raw data obtained from an experimental subject are a series of binary responses. In addition to the example of test item data we could include many questionnaire studies and psychological experiments involving discrimi­ nation, perception and the like. If the subjects are also classified on another variable, the design is similar to the split-plot design and is often called a two-factor repeated measures experiment by behavioral researchers. With continuous measurements which fit the normal model the analysis is fairly straightforward. Tests of the assumption of a patterned covariance matrix should be considered but results of Collier, et a/., (1967) indicate that moderate departures do not seriously invalidate the usual tests of significance. For situations in which the researcher feels that this "univariate" approach is unwarranted, a conservative test due to Greenhouse and Geisser (1959) or multivariate procedures described elsewhere e.g., Danford, et aL, (1960); Cole and Grizzle (1966) are appropriate. For dichotomous data, however, the literature provides few clues to aid the researcher. Recent non-parametric results of Koch (1969) which are based on ranks, are not directly applicable for dichotomous data. Other than the use

Journal

American Educational Research Journal – SAGE

Published: Jun 24, 2016

There are no references for this article.