Doug Roland

Some thoughts on the sensitivity of mixed models to (two types of) outliers

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Outliers are a nasty problem for both ANOVA or regression analyses, though at least some folks  consider them more of a problem for the latter type of analysis. So, I thought I post some of my thoughts on a recent discussion about outliers that took place at CUNY 2009. Hopefully, some of you will react and enlighten me/us (maybe there are some data, some simulations out there that may speak to the issues I mention below?). I first summarize a case where one outlier out of 400 apparently drove the result of a regression analysis, but wouldn’t have done so if the researchers had used ANO(C)OVA. After that I’ll have some simulation data for you on  another type of “outlier” (I am not even sure whether outlier is the right word): the case where a few levels of a group-level predictor may be driving the result. That is, how do we make sure that our results aren’t just due to item-specific or subject-specific properties. Read the rest of this entry »