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Some of these "toy" problems have had pretty major practical effects. For example, reconciling the disagreement between cohort studies and RCTs, in many medical
by Fomite 8y ago
Some of these "toy" problems have had pretty major practical effects. For example, reconciling the disagreement between cohort studies and RCTs, in many medical contexts, come down to remarkably simple causal diagrams.
- bachmeier 8y agoI don't disagree. I'm not debating the value of Pearl's approach. I'm saying other methods can also be helpful. Pearl does not accept that.
- kgwgk 8y agoWhat methods? His main point is that "To properly define causal problems, let alone solve them, requires a vocabulary that resides outside the language of probability theory. This means that all the smart and brilliant statisticians who used joint density functions, correlation analysis, contingency tables, ANOVA, Entropy, Risk Ratios, etc., etc., and did not enrich them with either diagrams or counterfactual symbols have been laboring in vain — orthogonally to the question — you can’t answer a question if you have no words to ask it." http://causality.cs.ucla.edu/blog/index.php/2018/06/11/statisticians-reaction-to-the-book-of-why/ http://causality.cs.ucla.edu/blog/index.php/2018/06/11/stati...