Repeated measures ANOVA: Difference between revisions

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Resource type: this resource contains a tutorial or tutorial notes.

Overview

The repeated measures design is also known as a within-subject design. In this design, participants may present scores for:

The same measure repeated over time
(e.g., self-confidence before, after, and following-up a psycho-social intervention), and/or
Across more than one condition
(e.g., experimental and control conditions), and/or
Several related and comparable factors
(e.g., sub-scales of an IQ test).

Repeated-measures designs can also be understood as an extension of the paired-samples t-test (to include comparison between more than two repeated measures).

Repeated-measures designs may also be combined with between-subjects factors to create mixed-design ANOVA. Multiple repeated-measures designs can also be tested using MANOVAs.

Why use?

By collecting data from the same participants under repeated conditions:

Individual differences can be reduced/eliminated as a source of between-groups differences (which helps to create a more powerful test).
Inferential testing becomes more powerful (the sample size is not divided between conditions/groups)

Possible designs

One-way repeated measures - repeated measures across one IV
Two-way repeated measures - repeated measures across two IVs
Two-way mixed split-plot design (SPANOVA) - repeated measures on one IV, independent groups on another IV

Assumptions

Most of the assumptions for between-subjects ANOVA design apply, however the key variation is Sphericity:

Instead of the homogeneity of variance assumption (which is part of one-way (between-subjects) and factorial ANOVA designs), repeated-measures designs have the assumption of sphericity, tested by Mauchly's sphericity test.
Sphericity means that the variance of the population difference scores for any two conditions should be the same as the variance of the population difference scores for any other two conditions.

External links

University of Canberra

Repeated measures ANOVA (ucspace)
- Repeated measures ANOVA Notes (Handout)

Other

Chapter 14 Within-Subjects ANOVA (HyperStat Online)

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@@ Line 23: / Line 23: @@
 ==Assumptions==
-Most of the assumptions for between-subjects ANOVA design apply, however the key variation is:
+Most of the assumptions for between-subjects ANOVA design apply, however the key variation is  '''Sphericity''':
-* '''Sphericity''': Instead of the homogeneity of variance assumption (which is part of one-way (between-subjects) and factorial ANOVA designs, repeated-measures designs have the assumption of sphericity, tested by [[w:Mauchly's sphericity test|Mauchly's sphericity test]].
+* Instead of the homogeneity of variance assumption (<small>which is part of one-way (between-subjects) and factorial ANOVA designs</small>), repeated-measures designs have the assumption of sphericity, tested by [[w:Mauchly's sphericity test|Mauchly's sphericity test]].
+* Sphericity means that the variance of the population difference scores for any two conditions should be the same as the variance of the population difference scores for any other two conditions.
 ==See also==

wikademia>Jtneill