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Consider an experiment where subjects reaction times are measured in three conditions. Because every subject participates in each condition, this is a typical within-subjects design. Now I'm wondering if a one-way within subjects anova is completely equivalent to a two-way anova with subject as the second factor. I already read some chapters on this topic but the difference between both procedures was never discussed explicitly.So,
- Is there an advantage of using one compared to the other?
- Is a multilevel approach with subject as the random effect and condition as a fixed effect even better?
- What if an effect of time is assumed, (e.g. fatigue). Could this be modelled additionally as a "third" factor?
I know these are pretty vague/broad questions but I hope you could give me some hints anyway.
Thanks in advance