Group Archives: Methods and methodology

Are systematic reviews simply adding to research waste?

What are some of the key current problems with systematic reviews – and what can we do about them?

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Mixed methods and corny metaphors

How often does “mixed methods” mean “mixed methods”? Not quite as often as we might hope…

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Did you catch the anglerfish? Navigating the depths of qualitative research

How should we go about presenting qualitative health services research which is rigorous, rich, but also able to be understood by a wide audience? Jenni Burt argues you should reach the depths, but maybe not tell everyone about it…

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Asking the right questions

One of the great things about Twitter is that you get to read other peoples’ takes on things. Matthew Hankins, for example, posts people’s interpretations of p-values (under the hashtag #stillnotsignificant), which are more entertaining than you might think. A few weeks ago he posted the conclusion from a paper which read: “we were quite …read more

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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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Interliteracy: The promise (and pitfalls) of multidisciplinary research

In her recent inaugural lecture as Professor of Sociology at Cambridge, Sarah Franklin referred to the idea of ‘interliteracy’, which she defines as ‘disciplined reading across disciplines.’ Franklin’s inclusion of ‘disciplined’ is important because it highlights the importance of rigour, strategy, and design when working across disciplines. What she has in mind when she speaks …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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What’s all the fuss about ‘big data’?

Big data seems to be the new catch word. What’s so special about it and why does it matter? ‘Big data’ refers to datasets so large that it becomes difficult to process them using conventional methods. Big datasets arise partly from ‘big science’, for example astrophysics and genetics. They also arise from measurements of human …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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