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One-Way Within-Subjects (Repeated Measures) ANOVA

One-way within-subjects ANOVA is also known as repeated measures analysis of variance, randomized-blocks one-way analysis of variance, single-factor within-subjects analysis of variance. As the subjects are exposed to each condition in turn, the measurement of the dependent (response) variable is repeated. The computed test statistic evalustes if there is a significant difference between at least two of the conditions of repeated measures in a set of k conditions.

Analysis Output

Accompanying Multiple Comparisons/Post-Hoc

Supported Worksheet Layout

For this ANOVA design, Aabel supports two different worksheet layouts.

• The layout I allows storing the design experimental scores (response data) from all of the k >= 3 conditions of repeated measures in a single numeric column, and uses the levels of the design single factor (A) to split the data accordingly. In this layout, a subject occurs in multiple worksheet rows: hence, it is required to have a data column (numeric or categorical) with the subject ID.
• The layout II requires storing the design experimental scores (response data) from each condition of repeated measures in a separate numeric column, i.e., each column represents one of the levels of the design (within-subjects) single factor.

The default output includes the two-way ANOVA table. The additional output depends on selected options, and can include the mean table, a mean bar plot, the results for sphericity test and correction, and table reports for selected multiple comparisons tests.

The error bars displayed on the interaction plots can represen:

• Standard error of mean
• Standard Deviation
• Confidence Interval (including options of 90.0%, 95.0%, 97.5%, 99.0%)

Sphericity Evaluation (Locally Best Invariant Test):

Sphericity implies that the variances of the differences between the repeated measurements should be approximately the same. However, within subjects analysis of variance is very sensitive to violations of the sphericity assumption. Therefore, sphericity tests and corrections are always provided with the repeated measures ANOVA.

• Comparing the power of different tests for sphericity, the Locally Best Invariant Test is recommended as having substantial power to detect departures from sphericity for both small and large samples and as providing good control of the Type I error.
• Aabel uses this test to evaluate whether or not the sphericity is tenable.

Greenhouse & Geisser and Huynd & Feldt Corrections:

• For sphericity corrections, Aabel provides Greenhouse & Geisser and Huynd & Feldt methods.

Simple comparisons (also know as pair-wise comparisons) accompanying one-way within-subjects ANOVA include:

• Tukey's HSD test (see the example above)
• Tukey B test on ordered means
• Fisher's LSD test
• The Newman-Keuls (Neuman-Keuls) test on ordered means
• Tukey Kramer test
• Scheffé test
• Bonferroni-Dunn test

The example below is the Tukey's HSD test result for the one-way within-subjects ANOVA example illustrated above.

For more information regarding multiple comparisons, click here.