Looking for Rigor in All the Wrong Places

What do the following ideas and practices have in common: unbiased estimation, statistical significance, insistence on random sampling, and avoidance of prior information? All have been embraced as ways of enforcing rigor but all have backfired and led to sloppy analyses and erroneous inferences. We discuss these problems and some potential solutions in the context of problems in social science research, and we consider ways in which future statistical theory can be better aligned with practice.

The seminar is held Thursday, February 23rd at the Economics Department, International Affairs Building (420 W. 118th Street) in room 1101, from 2:30 to 4:00 pm

I don’t have one particular paper, but here are a few things that people could read:

http://www.stat.columbia.edu/~gelman/research/published/rd_china_5.pdf

http://www.stat.columbia.edu/~gelman/research/unpublished/regression_discontinuity_16sep6.pdf

http://www.stat.columbia.edu/~gelman/research/published/retropower_final.pdf

Is there any chance that the talk will be recorded and/or published somewhere? I’m currently taking a statistics course that is covering these topics in the traditional way, and would love to learn more.

Open to the public?

+1

(If it is, I would like to come.)

Yup.

Cool. I’ll be the only economist there in a suit.

Yay! I’ll be there.

Thank you for an enlightening and enjoyable talk and discussion! I am glad I attended. (And I got to meet Jonathan [another one] in the elevator on the way out.)