-
Views
-
Cite
Cite
John P A Ioannidis, Modeling and Research on Research, Clinical Chemistry, Volume 60, Issue 9, 1 September 2014, Pages 1238–1239, https://doi.org/10.1373/clinchem.2013.218453
Close - Share Icon Share
Extract
Featured Article: Ioannidis JP. Why most published research findings are false. PLoS Med 2005;2:e124.5
The article featured here emerged as an effort to create an overarching modeling framework for proposed significant research findings and their validation, in line with accumulating empirical evidence on the replication rates of different types of research designs and settings. The main challenges behind the essay had occupied me and several other scientists over many years before its first draft was written in 2004.
Some initial impetus was offered by the advent of systematic approaches to evidence, such as systematic reviews and metaanalyses. Since the early 1990s, there was growing excitement that these approaches would allow piecing together the fragments of published literature and obtain summary results with higher accuracy and less uncertainty. In theory, this could revolutionize the translation of best science into best practice (1). For example, the Cochrane Collaboration adopted this vision (2) and was populated by volunteers with the noblest intentions for doing good—and no harm. Evidence-based medicine aimed to become the main new basic science of health (3).
