2024 Fall
11/08/2024: Introductory Text Analysis
Presenter: Megan Wisniewski
Location: Sociology Conference Room, McNeil 367, 3:00 – 4:00 PM
Material: [Presentation] |[Recording]
10/25/2024: Multiverse Analysis
Presenter: Kathryn O’Neill
Location: Sociology Conference Room, McNeil 367, 3:00 – 4:00 PM
Material: [Presentation] | [Reference paper] | [Codes]
2024 Spring
03/15/2024: Climate Data Introduction: A guide to access, process, and link with demographic data
Presenter: Kai Feng
Location: Sociology Conference Room, McNeil 367, 10:30 – 11:30 AM
Material: [github]
04/12/2024: Recentered Influence Function (RIF) regression and decomposition
Presenter: Andrew Kim (Post-doc, Population Studies Center)
Location: PSC Conference Room, McNeil Building 5th Floor, 1:30 – 2:30 PM
Material: [Presentation] | [Data & Codes]
04/26/2024: 1st Digital Korea Workshop at the Center for Korean Studies. We highlight here the main topics of two talks/workshops that are particularly relevant for us.
2:45 pm – 3:45 pm
Presenter: Jongyoon Baik (Post-doc, Center for the Study of Contemporary China)
Topic: Introduction to text analysis
4:00 pm – 5:00 pm
Presenter: Andrew Kim (Post-doc, Population Studies Center)
Topic: Data visualization using Stata [Presentation] & [Data & Code]
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”
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: 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:
-
- Caswell, Hal. 2019. The Formal Demography of Kinship: A Matrix Formulation. Demographic Research 41(24): 679-712.
- Caswell, Hal. 2020. The Formal Demography of Kinship II: Multistate Models, Parity, and Sibship. Demographic Research 42(38): 1097-1144
- Caswell, Hal. and Xi Song. 2021. The Formal Demography of Kinship III. Kinship Dynamics with Time-Varying Demographic Rates. Demographic Research 45(16):517-546.
- Caswell, Hal. 2022. The Formal Demography of Kinship IV: Two-Sex Models. bioRxiv.
Data: DemoKin Package on GitHub
11/02/2022: Modern Regression Discontinuity Designs (R Code) (Data)
Presenter: Michael Lachanski
Papers:
-
- Cattaneo, M. D., & Titiunik, R. (2022). Regression discontinuity designs. Annual Review of Economics, 14, 821-851.
- Cattaneo, M. D., Keele, L., & Titiunik, R. (2021). Covariate Adjustment in regression discontinuity designs. arXiv preprint arXiv:2110.08410.
- Cattaneo, M. D., Idrobo, N., & Titiunik, R. (2019). A practical introduction to regression discontinuity designs: Foundations. Cambridge University Press.
11/09/2022: Double/De-biased Machine Learning for Causal Inference (R Code)
Presenter: Cheney Yu
Papers:
-
- Chernozhukov, Victor, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey, and James Robins. 2018. “Double / Debiased Machine Learning for Treatment and Structural Parameters,” Econometrics Journal 21(1):1-68.
-
Felderer, B., Kueck, J., & Spindler, M. (2022). Using Double Machine Learning to Understand Nonresponse in the Recruitment of a Mixed-Mode Online Panel. Social Science Computer Review, 08944393221095194.
-
Robinson, Peter. 1988. “Root-N-Consistent Semiparametric Regression,” Econometrica 56(4):931-954.
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)
Papers:
-
- Kozlowski, A. C., Taddy, M., & Evans, J. A. (2019). The geometry of culture: Analyzing the meanings of class through word embeddings. American Sociological Review, 84(5), 905-949.
- Singular Value Decomposition Tutorial
12/07/2022: Dyadic Sequence Analysis (R Code)
Presenter: Allison Dunatchik
Papers:
-
- Liao, T, Bolano, D., Brzinsky-Fay, C., Cornwell, B., Fasang, A. E., Helske, S., Piccarreta, R., Raab, M., Ritschard, G., Struffolino, E., Studer, M. (2022) Sequence analysis: Its past, present, and future. Social Science Research.
- Liao, T. (2021) Using Sequence Analysis to Quantify How Strongly Life Courses Are Linked. Sociological Science
2022 Summer
08/30/2022: Computer Vision in the Social Sciences
Presenter: Doron Shiffer-Sebba
Papers:
-
- Torres, Michelle and Francisco Cantú. 2021. “Learning to See: Convolutional Neural Networks for the Analysis of Social Science Data.” Political Analysis 30(1): 113-131.
- Goldstein, Yoav, Nicolas M. Legewie, and Doron Shiffer-Sebba. 2022. “3D Social Research: Analysis of Social Interaction Using Computer Vision.” Sociological Methods and Research, Conditionally Accepted.
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
