It would be so easy to write a very similar article on why clinical laboratories show NOT use 'R' in their analyses. I use 'R' extensively for data presentatio

It would be so easy to write a very similar article on why clinical laboratories show NOT use 'R' in their analyses. I use 'R' extensively for data presentation, but I am constantly bitten by plots that look great, but do not in fact represent the data, because of some weird "factor" issue. I have never used a language where it is so easy to get beautiful results that are wrong. 'R' has very limited error checking, if it can figure out a way to do something (incorrectly), it's happy to do it. With its hidden 'statefulness' and tricky 'factor' effects, it would be a disaster in the clinical setting. Clinical labs need languages and procedures that will fail, rather than present an incorrect result. Unfortunately, 'R' does the opposite.