What is a Repeated Measures ANOVA?
Repeated-measures ANOVA is used when we have one group on which we measured something more than once. In other words, repeated measures designs, also known as within-subjects designs, can seem like oddball experiments. When you think of a typical experiment, you probably picture an experimental design that uses mutually exclusive, independent groups. These experiments have a control group and treatment groups that have clear divisions between them. Each subject is in only one of these groups.
When Should a Repeated Measures ANOVA Used?
GLM Repeated Measures is an ANOVA with repeated measures. We use ANOVA with repeated measures when we want to determine whether there is a difference between continuous variables measured multiple times in the same group of participants. For example, we want to determine whether exercise has an effect on weight loss in a group of 20 participants. Therefore, we will measure the weight of those participants before exercise, after 3 months of exercise, and after 6 months of exercise and we will compare the mean values of each group using an ANOVA with repeated measures.
An Example Of Repeated ANOVA
For example, a researcher wants to examine whether psychotherapy is beneficial. Therefore, it measures the level of anxiety before the start of psychotherapy, 3 months after psychotherapy, and 6 months after psychotherapy. Therefore, we have one variable – the level of anxiety, which we measure in three time periods.
What are the use of null and alternative hypothesis for the Repeated ANOVA?
Therefore, we test the following hypotheses:
Null hypothesis: There is no significant effect of psychotherapy on the level of anxiety.
Alternative hypothesis: There is a significant effect of psychotherapy on the level of anxiety.
R function to Compute Repeated Measures ANOVA
The code to run a repeated measures ANOVA using R is as follows:
aov (DV~ factor (time) + Error (factor (IV)), data = dataframe)
DV: dependent variable
IV: Independent variable