This week the BBC’s home editor, Mark Easton, reports on a new study examining the "harm" impacts of drugs in the UK, where there is ongoing debate about government drug policy and the issue of legalization. The study was a statistical analysis produced by the Independent Scientific Committee on Drugs, a group of scientists who believe the government’s current drug classification system is based on dogma rather than facts. It was published in the prestigious medical journal The Lancet.
At the heart of this study is a multivariate statistical analysis that evaluates 16 measures of personal and public "harm" caused by 20 legal and illegal drugs–from heroin and Ecstasy to alcohol and khat. Multivariate analysis is related to Monte Carlo simulation, and like that statistical technique incorporates sensitivity analysis.
You probably won’t be surprised to learn that the study finds the most "harm" comes from alcohol and the least from mushrooms, or that the authors conclude that "aggressively targeting alcohol harms is a a valid and necessary public health strategy."
On the way to these final judgments, there are some very interesting findings, and if only for the glitzy graphs representing the statistical analyses–and the current push to legalize marijuana in California–I recommend taking a look at Easton’s blog.
For some amusement and bemusement scroll down to the comments to the blog–e.g., "I especially like the ‘pink’ bits in the last diagram, ‘drug-specific imparement of mental functions’, which is presumably what you are actually paying for." These opinions demonstrate aptly that–statistical analysis, sensitivity regression analysis, Monte Carlo simulation–you can lay the facts on the line but no two people will look at them the same way.