Hi all,
Our next virtual meeting will be Wednesday, September 23, where we will
hear Reagan Mozer (Bentley University) presents research on "Recent
adventures in causal(ish) inference with text as data."
Abstract:
Text data have a long history in social science and education research.
However, these data are notoriously high-dimensional and characterized by
many nuances of language that lack plausible statistical models. As a
result, analysis of text data typically involves intensive human coding
tasks where particular constructs or features of the text are first
defined, and then a collection of documents are inspected and coded for the
presence or absence of these constructs. While this process may be feasible
in studies with smaller sample sizes, the time and resources required to
train and employ multiple human coders frequently poses a challenge for
large-scale efforts. In this talk, I will consider how to reliably and
efficiently extract meaningful constructs from text documents in a manner
that preserves human judgment, primarily for the purposes of supporting
causal inferences in randomized where some outcomes of interest are
features of text generated by the trial’s participants. To illustrate how
text data might be leveraged in various inferential settings both in and
out of the causal realm, I will present results from three recent studies
in education, medicine, and public health.
Zoom link:
https://harvard.zoom.us/j/99424949004?pwd=aWtPNFM3ZzFYbWxIMXNoZDlyUElVZz09
(Login
required)
When: Wednesday, September 23 at 12noon -- 1:30pm.
The information and schedule of the seminar can be found on our website
<https://projects.iq.harvard.edu/applied.stats.workshop-gov3009/home> and
Google calendar
https://bit.ly/30QZJ9k.
Best,
Soichiro Yamauchi
--
Soichiro Yamauchi
PhD candidate
Harvard University
URL:
https://soichiroy.github.io/