Social Science Quantitative Methods Reading Group
Coffee and snacks are provided courtesy of the Psychology Department.
| Date | Time | Building | Room | Topic |
|---|---|---|---|---|
| September 29th, 2023 | 4:00 PM | Kansas Union | Alderson Auditorium | Difference-in-Differences |
| October 27th, 2023 | 4:00 PM | Kansas Union | Centennial Room | Measurement Validation |
| December 1st, 2023 | 4:00 PM | Kansas Union | Kansas Room | Decomposition Models |
| January 26th, 2024 | 4:00 PM | Kansas Union | Alderson Auditorium | Time Series Statistics |
| February 23rd, 2024 | 4:00 PM | Kansas Union | Alderson Auditorium | Model Interpretation |
| March 29th, 2024 | 4:00 PM | Kansas Union | Alderson Auditorium | Natural Experiments |
| April 19th, 2024 | 4:00 PM | Kansas Union | Alderson Auditorium | Computational Modeling of Spatio-Temporal Processes |
Helpful links for upcoming reading groups.
March, 2024
1) Dobkin LM, Gould H, Barar RE, Ferrari M, Weiss EI, Foster DG. Implementing a prospective study of women seeking abortion in the United States: understanding and overcoming barriers to recruitment. Women's Health Issues. 2014 Jan-Feb;24(1):e115-23. doi: 10.1016/j.whi.2013.10.004.
2) Miller, Sarah, Laura R. Wherry, and Diana Greene Foster. 2023. "The Economic Consequences of Being Denied an Abortion." American Economic Journal: Economic Policy, 15 (1): 394-437.
3) Ingo E. Isphording, Marc Lipfert, Nico Pestel. Does re-opening schools contribute to the spread of SARS-CoV-2? Evidence from staggered summer breaks in Germany, Journal of Public Economics, Volume 198, 2021.
4) Fetzer T, Graeber T. Measuring the scientific effectiveness of contact tracing: Evidence from a natural experiment. Proc Natl Acad Sci U S A. 2021 Aug 17;118(33):e2100814118. doi: 10.1073/pnas.2100814118.
5) Barnett ML, Olenksi AR, Jena AB. Opioid Prescribing by Emergency Physicians and Risk of Long-Term Use. N Engl J Med. 2017 May 11;376(19):1896. doi: 10.1056/NEJMc1703338. PMID: 28489999.
February, 2024
1) Lundberg and Lee (2017). A unified approach to interpreting model predictions. 31st Conference on Neural Information Processing Systems.
2) Stenwig, E., Salvi, G., Rossi, P. S., & Skjærvold, N. K. (2022). Comparative analysis of explainable machine learning prediction models for hospital mortality. BMC Medical Research Methodology, 22(1), 1-14.
3) Link to webpage that explains the R package and methods implemented in Lundberg and Lee's 2017 paper: SHAPVIZ
Helpful links for past reading groups.
January, 2024
1) Webb, Linn, and Lego (2019). A Bounds Approach to Inference Using the Long Run Multiplier. Political Analysis 27:281-301.
2) Webb, Linn, and Lebo (2020). Beyond the Unit Root Question: Uncertainty and Inference. American Journal of Political Science 64(2): 275-292.
3) Slides, Stata Code, R Code, and Data
November/December, 2023
1) Fan, W. and L. Luo (2020). Understanding Trends in the Concentration of Infant Mortality among Disadvantaged White and Black Mothers in the U.S. 1983-2013. Demography 57:919-1005.
2) Prickett and Augustine, J (2021). Trends in Mothers Parenting Time by Education and Work 2003 - 2017. Demography 58(3): 1065-91.
October, 2023
1) Flake, J. K., & Fried, E. I. (2020). Measurement schmeasurement: Questionable measurement practices and how to avoid them. Advances in Methods and Practices in Psychological Science, 3(4), 456–465. https://doi.org/10/ghnbd
2) Cizek, G. J. (2016). Validating test score meaning and defending test score use: Different aims, different methods. Assessment in Education: Principles, Policy & Practice, 23(2), 212–225. https://doi.org/10.1080/0969594x.2015.1063479
September, 2023
Introduction to Difference-in-Differences (CFDR Workshop)
Paper on Difference-in-Differences (Wooldridge, 2021)
Mailing List
Use the link below to add your name to the email list for the University of Kansas Social Science Quantitative Methods Reading Group. This list will be used for updates about workshops and reading sessions organized by the Economic, Political Science, Psychology, and Sociology departments in coordination with the Kansas Data Science Consortium (KDSC).