Main effects as a by-product in a fixed effect 2 × 2 design, analyzed with ANOVA

Main effects as a by-product in a fixed effect 2 × 2 design, analyzed with ANOVA To study interaction effects, two sets of data are created for fixed effect ANOVA, both with combinatory effects of the two factors. In the first, both factors and their interaction contribute independently and directly to the dependent variable. In the second, each factor contributes indirectly to the dependent score. Data created with the first model can be analyzed flawlessly. The second often show relatively large main effects and relatively small interaction effects, and as a consequence the interaction effect may be rejected. Even when the dependent variable results solely from the multiplication of both factor scores, highly significant main effects can be obtained, while the interaction effect remains insignificant. Although mathematically correct, the relative contributions of the main effects are in that case difficult to interpret. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Main effects as a by-product in a fixed effect 2 × 2 design, analyzed with ANOVA

Loading next page...
 
/lp/springer_journal/main-effects-as-a-by-product-in-a-fixed-effect-2-2-design-analyzed-EZKcWD0E6q
Publisher
Springer Journals
Copyright
Copyright © 2004 by Kluwer Academic Publishers
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-005-2640-x
Publisher site
See Article on Publisher Site

Abstract

To study interaction effects, two sets of data are created for fixed effect ANOVA, both with combinatory effects of the two factors. In the first, both factors and their interaction contribute independently and directly to the dependent variable. In the second, each factor contributes indirectly to the dependent score. Data created with the first model can be analyzed flawlessly. The second often show relatively large main effects and relatively small interaction effects, and as a consequence the interaction effect may be rejected. Even when the dependent variable results solely from the multiplication of both factor scores, highly significant main effects can be obtained, while the interaction effect remains insignificant. Although mathematically correct, the relative contributions of the main effects are in that case difficult to interpret.

Journal

Quality & QuantitySpringer Journals

Published: Jan 26, 2005

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off