Clinical researchers too. Because lives are at stake.
The whole field of systematic reviews and meta-analyses has developed around the need to aggregate results from multiple studies of the same disease or treatment, because you can't just trust one isolated result -- it's probably wrong.
Statisticians working in EBM have developed techniques for detecting the 'file-drawer problem' of unpublished negative studies, and correcting for multiple tests (data-dredging). Other fields have a lot to learn...
Clinical researchers working for non-profits / universities do, occasionally. I suspect it has become popular recently not because lives are at stake, but because it lets you publish something meaningful without having to run complex, error prone and lengthy experiments.
Regardless of the true reason, these are never carried out before a new drug or treatment is approved (because there is usually one or two studies supporting said treatment, both positive).
And if you have pointers to techniques developed for/by EBM practitioners, I would be grateful. Being a bayesian guy myself and having spent some time reading Lancet, NEMJ and BMJ papers, I'm so far unimpressed, to say the least.
The whole field of systematic reviews and meta-analyses has developed around the need to aggregate results from multiple studies of the same disease or treatment, because you can't just trust one isolated result -- it's probably wrong.
http://en.wikipedia.org/wiki/Meta-analyses
Statisticians working in EBM have developed techniques for detecting the 'file-drawer problem' of unpublished negative studies, and correcting for multiple tests (data-dredging). Other fields have a lot to learn...