So, in a previous post I made a foray into the dangerous world of statistical models of meta-analysis. Now, I’ll try hard to explain why we need to start doubting random effects meta-analysis more than we often have done. […]
Category: critical appraisal note
It’s how mixed up? Meta analysis models step one.
Well, I have to start with an apology. In one of these columns, I foolishly claimed that the difference between a Peto OR fixed effect meta-analysis and a DerSimonian-Laird random effects meta-analysis was pointlessly academic. It’s not. Now, this might start getting all statistical, but there is a clear and important difference. Meta-analysis comes in […]
Hurtful or helpful?
When you’re thinking about applying the results of a clinical trial, its’ often difficult to get a meaningful handle on the balance that should be made between the beneficial and adverse effects of a treatment. If the medicine gives pain relief from your laparotomy to 1 extra patient in every three that take it (NNT=3), […]
Diagnostic tests: as easy as I, II, III
Diagnostic testing keeps coming back to bite Archi, and that’s not just because of a probability-based failure about a small relative and a missed diagnosis of congenital heart disease. No, the problem with diagnostic tests and their use and abuse remains difficult because the methods of research, the quality of research and the consequence of […]
Natural frequencies “keeping it real”
So, on hearing Matthew Thompson open up a mini-session with natural frequencies my mind turned to the healing power of crystals, and I become acutely concerned that the open-minds approach of the Teaching EBM Conference had gone too far. But this was quashed quickly by his description: […]
Dibbing
Well, the world of EBM teaching has once more benefited from the bilingual brilliance of Amanda Burls [@ajburls for the Tweeterati], in a superb hour-long lecture at the 16th Oxford Conference on Teaching Evidence Based Medicine. Gardening and teaching are not too different, it seems. The role of the facilitator is to encourage growth of […]
Unknowns: known, unknown and uncertain
Along with Rumsfelt, the drug-addled Dr. House and everyone who’s ever sat an exam, we can all recollect times when we know that we don’t know something. And we have times when we know something. And we have times when we learn about something we didn’t know we were unaware of. (Varenicline anyone?) And we […]
Many outcomes give no answer?
Some systematic reviews are confusing. Sometimes this is just poor writing style. Sometimes it’s because the techniques are difficult to grasp (meta-analytic item-response analysis, anyone?) And occasionally it’s because the data don’t seem to add up ‘right’. […]
“It ain’t what you say but the way that you say it”
Known and sung about from 1939 onwards, and beloved of puppy-trainers and parents of toddlers, it’s clear that how we say something is often more important than what we say. And we now know that this is true for how we write down clinical recommendations and indicate the weight of evidence behind them. (When I […]
It’s how ineffective?
In the last post I discussed the ‘p’ problem (not enuresis, which is subject to an upcoming NICE guideline) but statistical significance is only the first problem in deciding if something actually works. This post takes up the challenge of not just saying that something is likely to work, but just how well it works. […]