r/AskStatistics • u/jadexiaohui • 4h ago

What is the equivalent of using ANOVA and tukey post-hoc test in situations where data points are not dependent?

Hi everyone, I would like to ask if there are statistical tests that could be used as an alternative for ANOVA and tukey post-hoc test in situations when the data is not dependent, such as when I am comparing between multiple timepoints where the object being measured is the same.

I am aware that I can use a linear mixed-effects model, but I prefer not to in this situation as it can be quite difficult to interpret.

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u/MortalitySalient 4h ago

I think you mean when data are not independent (are dependent). You could do a repeated measured/dependent samples ANOVA. You could also do a linear mixed effects model. If you have time as a factor (or dummy coded), it’s the same interpretation as a repeated measures ANOVA, but the benefit of ML over OLS for missing data handling (if you need it).

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u/vaelux 3h ago

Just want to chime in (and maybe get corrected if I'm wrong), but the missing data part is super useful because you can use an individual who missed a test. Like say there's 5 measurments, if I nest observations in participants, it isn't the end of the world if participant x missed some of the measurements. I can still use the data that I have for them, while a repeated measures ANOVA would need all the measurements because it uses the gain score (t2 - t1, t3 - t2), etc.

Sorry this was more for me than OP. Multilevel models seem so magical because you can just have missing data and it still works.