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Mahanalobis Distance

A Reason to Not Drop Outliers

by Karen Grace-Martin  4 Comments

I recently had this question in consulting:

I’ve got 12 out of 645 cases with Mahalanobis’s Distances above the critical value, so I removed them and reran the analysis, only to find that another 10 cases were now outside the value. I removed these, and another 10 appeared, and so on until I have removed over 100 cases from my analysis! Surely this can’t be right!?! Do you know any way around this? It is really slowing down my analysis and I have no idea how to sort this out!!

And this was my response:

I wrote an article about dropping outliers.  As you’ll see, you can’t just drop outliers without a REALLY good reason.  Being influential is not in itself a good enough reason to drop data.

Tagged With: dropping outliers, influential outliers, Mahanalobis Distance, outliers

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