Dear Applied Statistics Community,

The applied statistics workshop begins this Wednesday (9/19) at 1200pm in N-354.  This workshop is billed as a tour of the applied statistics community at Harvard University, with scholars from Economics, Political Science, Public Health, Sociology, Statistics, and other fields coming together to present cutting edge research.  For our first talk,  Ben Goodrich (Government G-5) will present his work on Semi-Exploratory Factor Analysis.  Below is a summary of his presentation: 

 
I develop a new estimator called semi-exploratory factor analysis (SEFA)
that is slightly more restrictive than exploratory factor analysis (EFA)
and considerably less restrictive than confirmatory factor analysis.
SEFA has three main advantages over EFA: the objective function has a
unique global optimum, rotation is unnecessary, and hypotheses about
models can easily be tested. SEFA represents a very difficult
constrained optimization problem with nonlinear inequality constraints
that, for all practical purposes, can only be solved with a genetic
optimization algorithm, such as RGENOUD (Mebane and Sekhon 2007
[http://sekhon.berkeley.edu/papers/rgenoudJSS.pdf]). This use of new
features of RGENOUD is potentially fruitful for difficult optimization
problems besides those in factor analysis.

We have a preliminary schedule posted on the course website and please contact me (Justin Grimmer, jgrimmer@fas.harvard.edu) if you are interested in presenting in one of our few remaining open spots.  A light lunch will be provided and we encourage you to invite as many of your colleagues as possible.

 
Best,