Methods, Detection, Prevention and Examples
DO YOU KNOW WHICH LAW: Data sets obeying this law have approximately 30.1% of numbers start with a 1 whereas this percentage falls to 4.6% for the numbers starting with a 9.
– Clinical fraud – historical overview
– What are the consequences for Bio-Pharma?
– Why does fraud happen, and how often?
– How to detect fraud and sloppiness in clinical data?
– How to combat fraud with mitigation actions?
Curious how “the power of one” and “small number bias” help detect data manipulation and tampering in clinical research?
Spare yourself a fall-from-grace by so called ‘data detectives’. Implement RBQM, better sooner than later, and detect problems prior to publication. You might also like: How can RBQM spare organizations the trouble of retracting papers?