Should Basic Lab Experiments Be Blinded to Chip Away at the Reproducibility Problem?

An earlier version of this piece appeared on the Timmerman Report.

Note added 23Feb2016: Also realized that I was highly influenced by Regina Nuzzo’s piece on biases in scientific research (and solutions) in Nature, which has been nicely translated to comic form here.

Some people believe biology is facing a “Reproducibility Crisis.” Reports out of industry and academia have pointed to difficulty in replicating published experiments, and scholars of science have even suggested it may be expected that a majority of published studies might not be true. Even if you don’t think the lack of study replication has risen to the crisis point, what is clear is that lots of experiments and analyses in the literature are hard or sometimes impossible to repeat. I tend to take the view that in general people try their best and that biology is just inherently messy, with lots of variables we can’t control for because we don’t even know they exist. Or, we perform experiments that have been so carefully calibrated for a specific environment that they’re successful only in that time and place, and sometimes even just with that set of hands. Not to mention, on top of that, possible holes in how we train scientists, external pressures to publish or perish, and ever-changing technology.

Still, to keep biomedical research pushing ahead, we need to think about how to bring greater experimental consistency and rigor to the scientific enterprise. A number of people have made thoughtful proposals. Some have called for a clearer and much more rewarding pathway for reporting negative results. Others have created replication consortia to attempt confirmation of key experiments in an orderly and efficient way. I’m impressed by the folks at Retraction Watch and PubPeer who, respectively, call attention to retracted work, and provide a forum for commenting on published work. That encourages rigorous, continual review of the published literature. The idea that publication doesn’t immunize research from further scrutiny appeals to me. Still others have called for teaching scientists how to use statistics with greater skill and appropriateness and nuance. To paraphrase Inigo Montoya in The Princess Bride, “You keep using a p-value cutoff of 0.05. I do not think it means what you think it means.”

To these ideas, I’d like to throw out another thought rooted in behavioral economics and our growing understanding of cognitive biases. Would it help basic research take a lesson from clinical trials and introduce blinding in our experiments? Continue reading


Lack of replication no surprise when we’re studying really complex problems

All opinions are my own and do not necessarily reflect those of Novo Nordisk

For another nice take on this topic see Paul Knoepfler’s blog post here.

One of the sacred (can I say sacred in reference to something scientific?) tenets of the scientific method is reproducibility.  If something is real and measurable, if it’s a fact of the material world, then the expectation is that the result should be reproducible by another experimenter using the same methods as described in the original report.  One of the most well known (among physicists anyway) examples of irreproducible data is the Valentine’s Day Magnetic Monopole detected by Blas Cabrera back in 1982.  Great experimental data.  Never repeated, and therefore viewed as insufficient proof for the existence of a magnetic monopole.

So it’s troubling that in the past few years there have been numerous stories about the lack of reproducibility for different scientific experiments.  In biomedical science the number of  reports on the difficulty of reproducing results has gotten so great that the NIH has begun thinking about how to confirm and require reproducibility of some kinds of experimental results.  Just a few days ago another field, that of psychological priming, saw the publication of an article that the effects of “high-performance priming,” could not be reproduced.  This is another field undergoing serious questioning about whether/why results don’t reproduce, with commentary from such luminaries as Daniel Kahneman. Continue reading