Jonas Ranstam's website


6. Beware of ignorance markers


Some commonly used phrases reveal methodological ignorance and misunderstandings. If you plan to use these phrases, check that they are used in your intended sense. Here are a few problematic examples.

Phrase Problem

t-tests were used to "compare variables" Statistical hypothesis tests are used to test hypotheses about a population using data from a sample representing this population, not to describe the characteristics of the sample itself.

"independent samples" t-testsSeveral different t-tests have been developed for use with independent groups, e.g. Student's, Satterthwaite's, Welch's, Prien's t-tests and Hotelling's T-test.

normality was "assessed" using the Shapiro–Wilk testA variable's distribution in the population can perhaps be tested using a statistical hypothesis test but not be "assessed" until the entire population has been observed, which is not possible for unobservable populations.

"nonparametric data" A nonparametric hypothesis may be tested using a distribution-free test, but the phrase "nonparametric data" is nonsense.

"statistical difference" All differences are statistical in some sense.

"no difference" No clinically relevant difference or no statistically significant difference?

"significant difference" Does significant refer to uncertainty (statistical significance) or to relevance (clinical significance)?

"independently associated with"The effect estimates from a regression model used for estimating causal effects can only be interpreted on the basis of assumed cause-effect relationships among the included variables. No regression model would be necessary if independence is assumed.