Applied Statistics Workshop (Gov 3009)

The Applied Statistics Workshop (Gov 3009) meets all academic year, Wednesdays, 12pm-1:30pm, in CGIS K354. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers. There is a free lunch provided. Marc Ratkovic (Princeton) & Dustin Tingley (Harvard)- Sparse Estimation and Uncertainty with Application to Subgroup Analysis Title: Sparse Estimation and Uncertainty with Application to Subgroup Analysis Abstract: We introduce a Bayesian method, LASSOplus, that unifies recent contributions in the sparse modeling literatures, while substantially extending upon pre-existing estimators in terms of both performance and flexibility. Unlike existing Bayesian variable selection methods, LASSOplus both selects and estimates effects, while returning estimated confidence intervals among discovered effects. Furthermore, we show how LASSOplus easily extends to modeling repeated observations, and permits a simple Bonferroni correction to control coverage on confidence intervals among discovered effects. We situate the LASSOplus in the literature on exploring sub-group effects, a topic that often leads to a proliferation of estimation parameters. We also offer a simple pre-processing step that draws on recent theoretical work to estimate higher-order effects that can be interpreted independent of their lower-order terms. A simulation study illustrates the method’s performance relative to several existing variable selection methods. Application to an existing study of support for climate treaties illustrates the method’s ability to discover substantively relevant effects. Software implementing the method is made publicly available in the R package sparsereg.