Seminar Series - Dr. Connor Jerzak

Black and green network maps

Photo by Pietro Jeng on Unsplash

 

Event starts on this day

Mar

3

2023

Event starts at this time 2:00 pm — 3:00 pm
In Person & Virtual (view details)
Featured Speaker(s): Connor Jerzak
Cost: Free
Optimal Stochastic Interventions with High-Dimensional Factorial Experiments: Application to Conjoint Analysis

Description

The Spring 2023 SDS Seminar Series continues on Friday, March 3rd from 2:00 p.m. to 3:00 p.m. with Dr. Connor Jerzak (Assistant Professor at University of Texas at Austin). This event is in-person, but a virtual option will be available as well.

Title: Optimal Stochastic Interventions with High-Dimensional Factorial Experiments: Application to Conjoint Analysis

Abstract: Although there exists a rapidly growing literature on policy learning, much of the existing work focuses on the determination of an optimal treatment rule that determines who should be treated based on their individual characteristics. Instead, this paper studies the problem of finding an optimal intervention regime in high-dimensional factorial experiments. Our motivating application is conjoint analysis, which is popular in marketing and social science research. In one such experiment, respondents were asked to choose between hypothetical political candidates with randomly selected attributes, which include partisanship, policy positions, as well as candidate gender and race. Because the number of unique treatment combinations exceeds the total number of observations, it is impossible to identify the optimal treatment combination in this setting. Instead, we seek to find an optimal stochastic intervention, representing a probability distribution of treatments, that yields the greatest expected utility given variance constraints. We consider two classes of stochastic interventions. In the first, the optimal policy selection is performed in an average case sense---if respondents choose between one of two entities in a forced choice conjoint, we maximize the utility of a reference candidate averaging over features of the opponent. In the second, the optimal policy selection is performed in an adversarial manner in two rounds of selection---we maximize the support of a reference candidate against an opponent group which is also maximizing the support of their candidate in the same target population. We discuss several point estimate and variance-covariance estimators, some of which are obtained in closed form. Finite sample performance is explored via simulation. Our empirical analysis shows the usefulness of the proposed methodologies in the context of the US vote choice for president. 

Location

POB 2.302

Zoom

Please contact stat.admin@austin.utexas.edu for the zoom link.

Share


Audience

Other Events in This Series

Feb

17

2023

Seminar Series

Seminar Series - Dr. Yen-Chi Chen

Pattern Graphs: a Graphical Approach to Nonmonotone Missing Data

2:00 pm — 3:00 pm Virtual

Speaker(s): Yen-Chi Chen

Feb

24

2023

Seminar Series

Seminar Series - Dr. Antik Chakraborty

Bayesian inference on high-dimensional multivariate binary responses

2:00 pm — 3:00 pm Virtual

Speaker(s): Antik Chakraborty

Mar

10

2023

Seminar Series

Seminar Series - Dr. Baharan Mirzasoleiman

The Department for Statistics and Data Sciences at UT Austin presents its Spring 23 Seminar Series with speaker Dr. Baharan Mirzasoleiman.

 

 

2:00 pm — 3:00 pm Virtual

Speaker(s): Baharan Mirzasoleiman

Mar

24

2023

Seminar Series

Seminar Series - Dr. Lindsay Berry

The Department for Statistics and Data Sciences at UT Austin presents its Spring 23 Seminar Series with speaker Dr. Lindsay Berry

2:00 pm — 3:00 pm In Person & Virtual

Speaker(s): Lindsay Berry

Mar

31

2023

Seminar Series

Seminar Series - Dr. Mevin Hooten

Running on Empty:  Recharge Dynamics from Animal Movement Data

2:00 pm — 3:00 pm In Person & Virtual

Speaker(s): Mevin Hooten

Apr

7

2023

Graduate Talks

Ph.D. Program Poster Session

Ph.D. Poster Session

3:00 pm — 4:30 pm In Person

Speaker(s): PhD Students

Apr

14

2023

Seminar Series

Seminar Series - Dr. Eric Vance

Teaching Collaboration in Statistics and Data Science

2:00 pm — 3:00 pm In Person & Virtual

Speaker(s): Eric Vance

Apr

21

2023

Seminar Series

Seminar Series - Dr. Faming Liang

A Stochastic Neural Network Bridging from Linear Models to Deep Learning 

2:00 pm — 3:00 pm Virtual & In Person

Speaker(s): Faming Liang

May

5

2023

Seminar Series

CANCELED: Seminar Series - Dr. Ana-Maria Staicu

Spatial functional principal component analysis

2:00 pm — 3:00 pm In Person & Virtual

Speaker(s): Ana-Maria Staicu