This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Schuster, C. Articles by Von Eye, A. Search for Related Content Social Bookmarking                         What's this?

The Relationship of ANOVA Models with Random Effects and Repeated Measurement Designs

University of Notre Dame

Alexander Von Eye

Michigan State University

Understanding ANOVA models is often difficult because of the large amount of different experimental designs presented in applied textbooks.This article shows how different experimental designs arise out of the variation of three basic distinctions: block versus treatment factors, fixed versus random factors, and crossed versus nested factors.Once it is understood how each distinction influences the statistical analysis, the amount of experimental designs can be considerably reduced, because sometimes seemingly different experimental designs are essentially equivalent.This is shown by an example comparing a two-way analysis of variance model to a three-factor partially nested design.Furthermore, the way each distinction influences the statistical analysis of an experimental design can simplify the computational effort of the analysis because virtually every basic ANOVA procedure implemented in common statistical software packages can be used to fit more complex ANOVA models that are usually analyzed using special computer modules.

Journal of Adolescent Research, Vol. 16, No. 2, 205-220 (2001)
DOI: 10.1177/0743558401162006


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?