Hi everyone!
This week (the last meeting of the semester!) at the Applied Statistics
Workshop we will be welcoming *Jeff Gill*, Professor of Statistics and
Government at American University. He will be presenting work entitled *Models
for Identifying Substantive Clusters and Fitted Subclusters in Social
Science Data*. Please find the abstract below and on the Applied Stats
website here
<https://projects.iq.harvard.edu/applied.stats.workshop-gov3009>.
As usual, we will meet at noon in CGIS Knafel Room 354 and lunch will be
provided. See you all there!
-- Dana Higgins
*Title:* *Models for Identifying Substantive Clusters and Fitted
Subclusters in Social Science Data *
*Abstract:* Unseen grouping, often called latent clustering, is a common
feature in social science data. Subjects may intentionally
or unintentionially group themselves in ways that complicate the
statistical analysis of substantively important relationships. This work
introduces a new model-based clustering design which incorporates two
sources of heterogeneity. The first source is a random effect that
introduces substantively unimportant grouping but must be
accounted-for. The second source is more important and more difficult to
handle since it is directly related to the relationships of interest in the
data. We develop a model to handle both of these challenges and apply it
to data on terrorist groups, which are notoriously hard to model with
conventional tools.
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