2018Unpublished venueRequires access

Repeated Measures ANOVA

Daniel J. Denis

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Abstract

The chapter focuses on within-subjects designs or repeated measures that are used in cases where it makes sense to trace the measurement of an individual across conditions or time. These designs have analysis features that are distinct from the ordinary between-subjects designs. The chapter demonstrates the analysis of the repeated-measures data and shows how to interpret these models. It then describes a one-way repeated measures analysis of variance (ANOVA) and a two-way repeated measures ANOVA. In the chapter, a one-way repeated measures ANOVA is conducted on trial having three levels. Then, A 2 × 3 repeated measures ANOVA is performed, where treatment was the between-subject factor having two levels, and trial was the within-subjects factor having three levels. Repeated measures ANOVA violates the assumption of independence between conditions, and so an additional assumption is required of such designs, the so-called sphericity assumption. The chapter demonstrates how to evaluate this in SPSS.

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What this paper is about

The chapter focuses on within-subjects designs or repeated measures that are used in cases where it makes sense to trace the measurement of an individual across conditions or time. These designs have analysis features that are distinct from the ordinary between-subjects designs. The chapter demonstrates the analysis of the repeated-measures data and shows how to interpret these models. It then describes a one-way repeated measures analysis of variance (ANOVA) and a two-way repeated measures ANOVA. In the chapter, a one-way repeated measures ANOVA is conducted on trial having three levels. Then, A 2 × 3 repeated measures ANOVA is performed, where treatment was the between-subject factor having two levels, and trial was the within-subjects factor having three levels. Repeated measures ANOVA violates the assumption of independence between conditions, and so an additional assumption is required of such designs, the so-called sphericity assumption. The chapter demonstrates how to evaluate this in SPSS.

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Available abstract

The chapter focuses on within-subjects designs or repeated measures that are used in cases where it makes sense to trace the measurement of an individual across conditions or time. These designs have analysis features that are distinct from the ordinary between-subjects designs. The chapter demonstrates the analysis of the repeated-measures data and shows how to interpret these models. It then describes a one-way repeated measures analysis of variance (ANOVA) and a two-way repeated measures ANOVA. In the chapter, a one-way repeated measures ANOVA is conducted on trial having three levels. Then, A 2 × 3 repeated measures ANOVA is performed, where treatment was the between-subject factor having two levels, and trial was the within-subjects factor having three levels. Repeated measures ANOVA violates the assumption of independence between conditions, and so an additional assumption is required of such designs, the so-called sphericity assumption. The chapter demonstrates how to evaluate this in SPSS.

Key concepts: Repeated measures design, Mixed-design analysis of variance, Analysis of variance, Statistics, Mathematics, One-way analysis of variance, Sphericity, Variance (accounting)

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