PS 590

Fall 2023

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Research in Selected Topics
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Credit: 2 TO 12 hours.

Research in selected topics by arrangement with the instructor.

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CRN Type Section Time Day Location Instructor Section Details
10195
Independent Study
ARRANGED
n.a.
Location Pending
Part of Term:
1
Date Range:
08/21/23-12/06/23
Special Approval:
Instructor Approval Required
Section Info:
Register for PS 590 with individual instructor. CRNs vary by instructor.
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
51830
Online
CC1
1:00PM -3:00PM
W
n.a.
Bowers, J
Part of Term:
1
Date Range:
08/21/23-12/06/23
Credit:
4 hours
Section Title:
Making Causal Inferences
Section Info:
Making Causal Inferences: Statistical Inference and Adjustment for Randomized and Observational Studies. In this course we will introduce a way of learning about theoretical causal claims using research design and statistical inference that is tightly tied to the research design. We use research design to justify adjustment: For example, we might say that we do not worry about the potentially confounding effect of education in a study of a get out the vote policy because we used a randomized design. For another example, we might say that we do not worry about the potentially confounding effect of education in that study because only compare people who have the same education level — we match on education. When it comes time to calculate a p-value or confidence interval about counterfactual hypotheses or estimate an otherwise unobservable effect defined in counterfactual terms, this course will emphasize ways to justify choices of test and estimator using the research design used for adjustment in the first place as well as formal sensitivity analysis for observational studies. As currently envisioned, this course will introduce the basics of randomized experiments, instrumental variables, difference-in-differences, and matching on binary variables (bipartite matching), matching on continuous or multivalued variables (non-bipartite matching), matching with longitudinal data, and formal sensitivity analysis for observational studies. As currently envisioned, this course will introduce the basics of randomized experiments, instrumental variables, difference-in-differences, and matching on binary variables (bipartite matching), matching on continuous or multivalued variables (non-bipartite matching), matching with longitudinal data, and formal sensitivity analysis. I will be open to adding and subtracting topics depending on student interest.
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
Restricted to PHD:Political Science -UIUC.
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