When repeated measures are used which assumption is violated?

When repeated measures are used which assumption is violated?

assumption of sphericity
Unfortunately, repeated measures ANOVAs are particularly susceptible to violating the assumption of sphericity, which causes the test to become too liberal (i.e., leads to an increase in the Type I error rate; that is, the likelihood of detecting a statistically significant result when there isn’t one).

Which assumption of normality do we violate In repeated measure ANOVA?

Repeated-measures ANOVA should not be conducted when the assumption of normality of difference scores is violated. Repeated-measures ANOVA should only be conducted on normally distributed continuous outcomes.

What do you need for a repeated measures ANOVA?

The repeated measures ANOVA compares means across one or more variables that are based on repeated observations. A repeated measures ANOVA model can also include zero or more independent variables. Again, a repeated measures ANOVA has at least 1 dependent variable that has more than one observation.

When can you not use a repeated measures ANOVA?

In other words, you want to treat the within-subjects effect of time as a continuous, quantitative variable. This is theoretically valid and reasonable, but repeated measures ANOVA can only account for categorical repeats.

What is a three way repeated measures ANOVA?

The three-way repeated measures ANOVA is used to determine if there is a statistically significant interaction effect between three within-subjects factors on a continuous dependent variable (i.e., if a three-way interaction exists).

What is sphericity assumption in ANOVA?

Sphericity is an important assumption of a repeated-measures ANOVA. It is the condition where the variances of the differences between all possible pairs of within-subject conditions (i.e., levels of the independent variable) are equal.

What is the normality assumption?

In technical terms, the Assumption of Normality claims that the sampling distribution of the mean is normal or that the distribution of means across samples is normal.

What is a repeated measures design what are the advantages of using a repeated measures design what are the disadvantages?

Repeated measures designs have some disadvantages compared to designs that have independent groups. The biggest drawbacks are known as order effects, and they are caused by exposing the subjects to multiple treatments. Order effects are related to the order that treatments are given but not due to the treatment itself.

Why is repeated measures ANOVA more powerful?

More statistical power: Repeated measures designs can be very powerful because they control for factors that cause variability between subjects. Fewer subjects: Thanks to the greater statistical power, a repeated measures design can use fewer subjects to detect a desired effect size.

Is repeated measures ANOVA a parametric test?

It is analagous to Repeated Measures ANOVA, but with the advantage of being non-parametric, and not requiring the assumptions of normality or homogeneity of variances. However, it has the limitation that it can only test a single explanatory variable at a time.

What is two-way repeated measures ANOVA?

For Two-Way Repeated Measures ANOVA, “Two-way” means that there are two factors in the experiment, for example, different treatments and different conditions. “Repeated-measures” means that the same subject received more than one treatment and/or more than one condition.