Hi all,
Our next virtual meeting will be at 12pm (EST) Wednesday, March 24
(tomorrow), where Avi Feller (UC Berkeley) will present "Varying impacts of
letters of recommendation on college admissions: Approximate balancing
weights for subgroup effects in observational studies." This is joint work
with Eli Ben-Michael and Jesse Rothstein.
*Abstract*:
In a pilot program during the 2016-17 admissions cycle, the University of
California, Berkeley invited many applicants for freshman admission to
submit letters of recommendation. We use this pilot as the basis for an
observational study of the impact of submitting letters of recommendation
on subsequent admission, with the goal of estimating how impacts vary
across pre-defined subgroups. Understanding this variation is challenging
in observational studies, however, because estimated impacts reflect both
actual treatment effect variation and differences in covariate balance
across groups. To address this, we develop balancing weights that directly
optimize for "local balance'' within subgroups while maintaining global
covariate balance between treated and control units. We then show that this
approach has a dual representation as a form of inverse propensity score
weighting with a hierarchical propensity score model. In the UC Berkeley
pilot study, our proposed approach yields excellent local and global
balance, unlike more traditional weighting methods, which fail to balance
covariates within subgroups. We find that the impact of letters of
recommendation increases with the predicted probability of admission, with
mixed evidence of differences for under-represented minority applicants.
*Zoom link*:
https://harvard.zoom.us/j/97787602526?pwd=Uzh3bVVVS0F4TEVYQTJlV3BQNjcydz09
*Schedule of the workshop*:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Looking forward to seeing you all tomorrow!
Best,
Soichiro
--
Soichiro Yamauchi
PhD candidate
Harvard University
URL:
https://soichiroy.github.io/