Events

2022 Fall

The Methodology Working Group workshops are held on Wednesdays from 10:30-11:30 am.

09/21/2022: An Introduction to Neural Networks
Presenters: Bhuv Jain and Dimitrios Tanoglidis
Resources: https://github.com/dtanoglidis/ML_Edu_Demos/blob/main/UPenn_Methodology_DL.ipynb & https://github.com/dtanoglidis/ML_Edu_Demos

10/12/2022: FSRDC Data Types & Becoming a Special Sworn Status Researcher
Presenters: Joe Ballegeer (U.S. Census Bureau) and Jeff Lin (U.S. Census Bureau)

10/19/2022: Nonstable Population Relations and Applications in Aging, Labor, Health, Immigration (R Code)
Presenter: Michael Lachanski

10/26/2022: Kinship Estimation Using the DemoKin Package in R (R Code)
Presenters: Hal Caswell (University of Amsterdam) and Kai Feng
Papers:

Data: DemoKin Package on GitHub

11/02/2022: Modern Regression Discontinuity Designs (R Code) (Data)
Presenter: Michael Lachanski

Papers:

 

11/09/2022: Double/De-biased Machine Learning for Causal Inference (R Code

Presenter: Cheney Yu

Papers:

11/16/2022: Marginal Structural Models (R Code) (Data)
Presenter: Sukie Yang

11/30/2022: Word Embedding Using Occupation Data
Presenter: Wenhao Jiang (NYU)

12/07/2022: Dyadic Sequence Analysis
Presenter: Allison Dunatchik

2022 Summer

08/30/2022: Computer Vision in the Social Sciences
Presenter: Doron Shiffer-Sebba
Papers:

06/21/2022: Estimation Philosophy
Presenters: Michael Lachanski & Richard Patti
Paper:
Lundberg, Ian, Rebecca Johnson, and Brandon M. Stewart. 2021.”What Is Your Estimand? Defining the Target Quantity Connects Statistical Evidence to Theory.” American Sociological Review 86(3):532-65. 

06/10/2022: GitHub for Research Reproducibility and Transparency
Presenter: Hunter York

06/07/2022: Spatial Bayesian Regression (R Code) (Data)
Presenters: Treva Tam & Eugenio Paglino
Paper:
Morris, Mitzi, Katherine Wheeler-Martin, Dan Simpson, Stephen J. Mooney, Andrew Gelman, and Charles DiMaggio. 2019. “Bayesian Hierarchical Spatial Models: Implementing the Besag York Mollié Model in Stan.” Spatial and Spatio-temporal Epidemiology 31:100301. [Alternative Access via Research Gate]
Book: Blangiardo, Marta, and Michela Cameletti. 2015. Spatial and Spatio-Temporal Bayesian Models with R-INLA. Chichester, England: Wiley. [Penn Libraries Online Access]

05/24/2022: Difference-in-Differences (Introduction) (R Code)
Presenter: Alexander Adames
Paper:  Angrist, Joshua D. and Jörn-Steffen Pischke. 2009. “Chapter 5: Parallel Worlds: Fixed Effects, Difference-in Differences, and Panel Data Angrist.” Pp. 221-246 in Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton. NJ: Princeton University Press. [Penn Libraries Online Access]

2020

05/29/2020: Data Visualization Mini-Hackathon