# Repeated measures ANOVA (and Friedman)

** Dependent (outcome) variable: ** Continuous/numerical/scale (some disciplines also test ordinal data)

** Independent (predictor/explanatory) variable: ** Time or condition (3+ levels)

**Use: **Tests the equality of means in 3 or more groups. All sample members characteristics must be measured under multiple conditions i.e. the dependent variable is repeated. This is the equivalent of a one-way ANOVA but for repeated samples and is an extension of a paired-samples t-test. It is used to analyse (1) changes in mean score over 3 or more time points (2) differences in mean score under 3 or more conditions.

**Example:** Test the effectiveness of a margarine for reducing cholesterol by comparing participants cholesterol before a trial to their cholesterol after 4 weeks and again after 8 weeks of using the margarine.

** Assumptions:** *The dependent variable (or residuals) should be approximately normally distributed at each level . If a histogram or QQplot suggests the residuals are vey skewed or the dependent variable is ordinal, a Friedman test (which is based on ranks rather than the raw data) should be used. Some people use parametric tests for ordinal data if there are quite a few categories but be careful when interpreting differences*

** Data notes ** Ensure there is one row per participant with a different column for the dependent variable for each condition/time point.

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