Author Archives: Gary Abel

Is formally testing for normality largely a waste of time?

A common assumption of many statistical techniques is that the data are conditionally normally distributed. For example, an assumption made when performing a t-test is that the variable being tested is normally distributed in each group. In the example of linear regression, one of the assumptions is that the residuals are normally distributed. Clearly it …read more

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Significantly significant?

A complaint often levelled at medical research is that far more focus is given to statistical significance than clinical significance. In fact I saw a tweet a few weeks ago deploring the situation. This made me think why this is the case. The short answer is that we have some fairly well established thinking about …read more

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What is so special about random effects?

Nothing! Apologies for the rather glib answer, but this blog is not aimed at my fellow statisticians for whom issues around power, parsimony, computational efficiency, and distributional assumptions keep them awake at night. Nor should these issues be ignored when we are thinking about the design of a study or the analysis methods to use. …read more

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Joint tests: What are they and why use them?

Recently I have been asked to explain what was meant by the term “Joint test” by reviewers or editors of papers under consideration for publication. This has surprised me somewhat as in most cases joint tests are the most appropriate test for the effect of categorical variables and should be commonplace. However, they are not …read more

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