{"id":926,"date":"2014-05-14T20:33:00","date_gmt":"2014-05-14T19:33:00","guid":{"rendered":"http:\/\/stg-blogs.bmj.com\/adc\/?p=926"},"modified":"2014-05-14T16:02:52","modified_gmt":"2014-05-14T15:02:52","slug":"underpowered-and-over-here","status":"publish","type":"post","link":"https:\/\/stg-blogs.bmj.com\/adc\/2014\/05\/14\/underpowered-and-over-here\/","title":{"rendered":"Underpowered and over here."},"content":{"rendered":"
\"\"
From @aLittleMedic<\/figcaption><\/figure>\n

We’re great fans in the Archimedes blog of trying to get people to think about the meanings and impacts of research, like asking What would Jack want <\/a>and not believing p-values. <\/a>One key idea is that of an ‘important clinical difference<\/a>‘ (see – avoided significantly …) that is essential in working out if a trial\u00a0is telling you two treatments really are equivalent, or if the study is just underpowered.<\/p>\n

If you’re designing a trial you’ll be wanting to be very very sure that this difference, that you’re gong to base all your study numbers upon is, made upon the best possible grounds. Aren’t you.<\/p>\n

<\/p>\n

Which is why a recent systematic review<\/a> of methods to determine this value – the DELTA group review – is really interesting reading. They identified papers which used variants of seven approaches, six of which address the idea of an ‘important’ difference:<\/p>\n