Replication Crisis - quantification of uncertainty

[TomBAvoider]

So, as is well known, the majority of biomedical studies will not stand the test of time, and the vast majority are likely simply false. That means, that whenever you read a new study, odds are, it's invalid. Here is the case laid out:

https://www.ahajournals.org/doi/10.1161/CIRCRESAHA.114.303819

"Abstract

Medical and scientific advances are predicated on new knowledge that is robust and reliable and that serves as a solid foundation on which further advances can be built. In biomedical research, we are in the midst of a revolution with the generation of new data and scientific publications at a previously unprecedented rate. However, unfortunately, there is compelling evidence that the majority of these discoveries will not stand the test of time. To a large extent, this reproducibility crisis in basic and preclinical research may be as a result of failure to adhere to good scientific practice and the desperation to publish or perish. This is a multifaceted, multistakeholder problem. No single party is solely responsible, and no single solution will suffice. Here we review the reproducibility problems in basic and preclinical biomedical research, highlight some of the complexities, and discuss potential solutions that may help improve research quality and reproducibility."

Meanwhile there is a fascinating article detailing some of the issues surrounding the quantification of uncertainty as a key factor in the crisis:

http://nautil.us/issue/74/networks/the-flawed-reasoning-behind-the-replication-crisis

Edited August 7, 2019 by TomBAvoider
emphasis