Tag Archives: Statistics explained

What do patient experience, genome-wide association studies and randomised controlled trials have in common? A blog about p-values

As far as I understand, genome-wide association studies (GWAS) have been a very successful approach to looking at huge numbers of possible associations of genes with different medical problems. The approach is broadly “hypothesis free” without specific prior reasons to think that any single genetic change out of the millions considered might be associated. This …read more

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Big data

With big data arriving on the scene for health care, we can take a slightly smaller look at some of data on health service performance that is increasingly being made public in the UK. What does it mean for me as a patient? Well it means that there are now lots of websites where you …read more

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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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Ecological fallacy and Wikipedia

I really do like Wikipedia. Following up on my post about correction for attenuation, Wikipedia is also quite good on ecological fallacy (that you can’t make inference at the individual level from data observed at the population level). Their example at the moment is nice too. Rich states voted for Kerry in the 2004 US …read more

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Correction for attenuation (via Wikipedia)

If you are Charlotte or Yoryos (who I work for) then honestly I don’t just present work off Wikipedia and pretend it is my own. Anyone else, this article about correction for attenuation is quite good. Unless of course, by the time you read it has been edited into an entirely different form, which is …read more

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