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Early stage research often gets dinged for not including enough trial subjects to be statistically valid. But adhering to the large sample-size dogma is counterproductive, says Peter Bacchetti, a biostatistician at the University of California, San Francisco. Large sample sizes waste time on unsuccessful ideas as most early stage trials fail, and can even prevent innovative treatments from moving forward if trials that don't recruit enough patients are never performed, he argues in a perspectives piece published online today (June 15) in Science Translational Medicine.
This week, Bacchetti took time to speak with The Scientist about why sample size isn’t everything, and what scientists can use instead to measure a study’s worth.
The Scientist: Why does starting small make sense?
Peter Bacchetti: Because you don’t ...
