Cognitive Lunch Abstract for January 21

The next Cognitive Lunch will be held Wednesday, January 21.
Time: 12:10-1:10 p.m.
Place: Psychology Conference Room (room 128)

"Model Selection for Dummies" will be presented by Rich Shiffrin, Department of Psychological and Brain Sciences.

Abstract:
Model selection in the narrow sense is best viewed as statistical inference, although there are many larger concerns as well. Although a non-expert, I have been involved with many of the modern developments in this area, and even published (with Andrew Cohen and Adam Sanborn) a recent PB&R article on the subject. Access to this field for non-experts is a daunting task, due to technical gimcrackery, uninterpretable terminology, non-stop argumentation among experts about the 'right approach', and mixtures of philosophical, mathematical, and empirical justifications for the alternative approaches. Yet statistical inference in the modern age absolutely requires the use of these modern approaches. Thus scientists are increasingly using model selection techniques, mostly in the form of such simple approximations as AIC and BIC, often without understanding the inference issues that are involved. Even experts can lose their way and lose sight of the basic underlying conceptual issues, and non-experts often cannot find their way at all. In this cognitive lunch talk I will discuss some of the larger model selection issues, but spend most of the time on the narrow issue of statistical inference. The exposition will be almost entirely non-technical (certainly by the standards of this field), but will nonetheless focus on the two or three leading modern approaches to model selection. I hope to illuminate the core conceptual issues. (There will be ample room for experts to express their horror at any mis-characterizations I introduce, but with luck, even experts may find a few nuggets of wisdom in the discussion).