Causal Inference from Experimental Data (30th R A Fisher Memorial Lecture)
Seminar Room 1, Newton Institute
One of the greatest scientific advances of the 20th Century was not substantive, but methodological: the laying out by Fisher of the principles of sound experimentation, so allowing valid conclusions to be drawn about the effects of interventions - what we must surely regard as "causal inference". More recently "causal inference" has developed as a major enterprise in its own right, with its own specialist formulations and methods; however, these owe more to Neyman than to Fisher. In this lecture I shall explore the connexions and contrasts between older and newer ideas in causal inference, revisit an old argument between Neyman and Fisher, and argue for the restructuring of modern theories of causal inference along more Fisherian lines.