We all know that "correlation does not equal causation" but it is still counterintuitive. There are many questions in healthcare that just cannot be approached by the randomized controlled trial (RCT) requiring us to depend on observational data which is extremely susceptible to this confounding correlation problem. Are there any visual tools that we can use to help keep our thinking honest and not fall for spurious correlations? YES! Join us on an exploration of directed acyclic graphs!!! THIS ARTICLE IS CURRENTLY OPEN ACCESS SO FOLLOW THE LINK TO READ IT!

Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data. Rohrer JM. Advances in Methods and Practices in Psychological Science. First Published January 29, 2018.

Here is the Amazon link to the book Erik was talking about, Anathem by Neal Stephenson. Due to copyright laws, unless the article is open source we cannot legally post the PDF on the website for the world to download at will. That said, if you are having difficulty obtaining an article, contact us.

Music for PT Inquest: "The Science of Selling Yourself Short" by Less Than Jake Used by Permission

119 Thinking Clearly About Correlations and Causation