Currently viewing the tag: "Aaron E. Carroll"
From a Painting By Numbers perspective, the article below is probably one of the most important you’ll read this month, maybe the next few months.
It does a great job expanding on my Commandment No. 10, “Respect the Human Condition,” probably the most sweeping of the twelve commandments in my book. It means that the foibles of us mere mortals – such as accentuating the positive, stretching for success, seeking reward and avoiding punishment – are almost always baked into every numerical result we see in the public sphere. And when they aren’t, you can bet it took lots of experts with plenty of patience for the foibles, or biases, to be extracted out.
Unless you are looking at primary research documents, every numerical result you see has two major components: the work of the analysts or researchers themselves and the work of those (journalists, communications professionals, policy aids, etc) who report them. The headline of the article below focuses on making the scientific method better account for less than positive results. But the authors also take reporters to task, who generally ignore critical research which doesn’t lead to a positive result.
The headline, “Dope a Trope shows modest cancer fighting ability in latest research,” is going to have higher readability than “Scientists find Dope a Trope has no effect on cancer patients.” The problem with this is, in the realm of research, there could be half a dozen experiments of the latter variety and only one of the former. And the half dozen who found no effect probably aren’t going to impress those who fund research.
The author, Aaron E. Carroll of the Indiana University School of Medicine, notes, rightly I believe, that the whole culture of professional scientific research has to change to address this endemic challenge. Thankfully, the author has a great blog site, The Incidental Economist, where he regularly expands on this broad but critical subject. For those interested in diving in even deeper, The Center for Open Science has tools and info for making research methods more transparent and results more reproducible. Only after many experts arrive at the same results should the rest of us even begin to take them seriously.
https://www.nytimes.com/…/science-needs-a-solution-for-the-…
