2023 Fall

If you are interested in taking part in the group, please share your contact information and indicate your time availability for Fall 2023 meetings by filling out this form.

Oct. 26, 2023 at 12:00 PM – 1:00 PM | PSC Conference Room, McNeil 5th floor
Eugenio Paglino, Ph.D. Student in Sociology and Demography, Penn
“A primer on small-area estimation: a case study on mortality in Massachusetts Census tracts”

Nov 9, 2023 at  –  | PSC Conference Room (McNeil Building, 5th Floor)
Tim Riffe, Research Fellow, Research Group in Social Determinants of Health and Demographic Change (OPIK) of the University of the Basque Country (UPV/EHU)
“Demographic Decomposition Workshop”


2023 Spring

The Methodology Working Group meets this Spring from 2-3:30pm on Mondays in McNeil 367 (the Sociology Conference Room).

01/30/2023: Using UPenn SAS High Performance Computing/Slurm Scheduler and PSCStat for Computationally Intensive Research
Presenter: Xi Song

02/09/2023: Introduction to the PSID
Presenter: Paula Fomby
**NOTE: This presentation will take place on Thursday, February 9th from 2 – 3:30pm in McNeil 367

02/13/2023: Introduction to Supervised Machine Learning (Python Code) (Data)
Presenter: Rebecca Johnson (Assistant Professor of Public Policy, Georgetown University)

02/20/2023: Causal mediation analysis
Presenter: Nick Graetz

02/27/2023: Polynomial Regression with Response Surface Analysis
Presenter: Kuo Zhao

03/20/2023: Matching Methods
Presenter: Alexander Adames

03/27/2023: Regression Discontinuity Design
Presenter: Sneha Mani

04/03/2023 Introduction to the LIFE-M Database
Presenter: Paul Mohnen

04/10/2023:  Embracing Essential Discourse in Educational Policy about Causal Inferences from Observational Studies: Towards Pragmatic Social Science
Presenter: Ken Frank (Michigan State University)
Co-sponsored with the Education and Inequality Working Group

04/17/2023: Semantic Network Analysis
Presenter: Alejandra Regla-Vargas

04/24/2023: Computational Demography in R (tentative)
Presenter: Michael Lachanski (tentative)

05/01/2023: Shift-share instruments (tentative)
Presenter: Michael Lachanski (tentative)

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: &

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

Data: DemoKin Package on GitHub

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


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

Presenter: Cheney Yu


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

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


12/07/2022: Dyadic Sequence Analysis (R Code)
Presenter: Allison Dunatchik


2022 Summer

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

06/21/2022: Estimation Philosophy
Presenters: Michael Lachanski & Richard Patti
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
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]


05/29/2020: Data Visualization Mini-Hackathon