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The Problem with Using Tests for Statistical Assumptions - The Analysis Factor

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And yes, if you’re going to use a statistical test, you need to check whether those assumptions are reasonable to whatever extent you can. Some assumptions are easier to check than others. Some are so obviously reasonable that you don’t need to do much to check them most of the time. And some have no good way of being checked directly, so you have to use situational clues. There are so many nuances with assumptions as well: depending on a lot of the details of your particular study and data set, violations of some assumptions may be more or less serious. It depends on a lot of details: sample sizes, imbalance in the data across groups, whether the study is exploratory or confirmatory, etc. And here’s the kicker: the simple rules your stats professor told you to use to test assumptions were absolutely sufficient when you were learning about tests and assumptions. But now that you’re doing real data analysis? It’s time to dig into the details. So here are some guidelines about checking a

Every statistical model and hypothesis test has assumptions. And yes, if you’re going to use a statistical test, you need to check whether those assumptions are reasonable to whatever extent you can. Some assumptions are easier to check than others. Some are so obviously reasonable that you don’t need to do much to check them most of the time. And some have no good way of being checked directly, so you have to use situational clues. There are so many nuances with assumptions as well: depending on a lot of the details of your particular study and data set, violations of some assumptions may be

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