Causality reading group

The focus of the Leiden causality reading group is on mathematical theory for causal inference, with some meetings dedicated to methodological developments. The reading group meetings take place on Mondays, 16.00-17.30, and are open to all. For the time being, the meetings will take place online. If you’d like to be added to the mailing list, please send me an e-mail.

Another online seminar on causal inference is available here.

The schedule (list of papers to consider for future discussion below):

Date Location Topic Materials Speaker
November 23, 2020 Online Bayesian nonparametric modeling, based on:
Hill (2011). Bayesian nonparametric modeling for causal inference.
Hahn, Murray, Carvalho (2020). Bayesian regression tree models for causal inference: regularization, confounding, and heterogeneous effects.
Ray, Van der Vaart (2020+). Semiparametric Bayesian causal inference.
Ray, Szabo (2019). Debiased Bayesian inference for average treatment effects.
  Aad van der Vaart
November 2, 2020 Online Young, Stensrud, Tchetgen Tchetgen, Hernán (2020). A causal framework for classical statistical estimands in failure time settings with competing events.   Richard Post
October 12, 2020 Online Goetghebeur, Le Cessie, De Stavola, Moodie, Waernbaum (2019+). Formulating causal questions and principled statistical answers.   Saskia le Cessie
September 28, 2020 Online Van Geloven, Swanson, Ramspek, Luijken, Van Diepen, Morris, Groenwold, Van Houwelingen, Putter, Le Cessie (2020). Prediction meets causal inference: the role of treatment in clinical prediction models.   Nan van Geloven
March 9, 2020 Snellius, room 176 Robins, Rotnitzky (1995). Semiparametric efficiency in multivariate regression models with missing data.   Lasse Vuursteen
February 24, 2020 LUMC building 2, T-00-022 Diemer, Labrecque, Tiemeier, Swanson (2020). Application of the instrumental inequalities to a Mendelian randomization study with multiple proposed instruments. Background on Mendelian randomization: video & article Sonja Swanson, Lizzie Diemer
February 10, 2020 LUMC building 2, T-00-022 Toh and Hernán (2008). Causal inference from longitudinal studies with baseline randomization.   Bart Eggen
December 9, 2019 LUMC building 2, T-00-022 Abadie and Imbens (2005). Large sample properties of matching estimators for average treatment effects.   Aad van der Vaart
November 25, 2019 LUMC building 3, V-04-018/022 Joint Causal Inference from Multiple Contexts   Joris Mooij
November 4, 2019 LUMC building 3, V-02-018/022 Hernán (2010). The hazard of hazard ratios.
Aalen, Cook and Røysland (2015). Does Cox analysis of a randomized survival study yield a causal treatment effect? 
slides Hein Putter
October 14, 2019 LUMC building 3, V-04-052/056 Caliendo and Kopeinig (2005). Some practical guidance for the implementation of propensity score matching. slides 1
slides 2
notes Rubin
Stéphanie van der Pas
May 27, 2019 LUMC building 3, V-03-036 Pearl, Chapters 9 and 10. slides Amine Hadji
May 13, 2019 LUMC building 2, T-00-022 Pearl, Chapter 8.   Richard Gill
April 8, 2019 LUMC building 3, V-02-018/022 Peters et al, Chapter 9. slides Stefan Franssen
March 25, 2019 LUMC building 3, V-02-034 Peters et al, Chapters 4 and 7. slides Richard Post
March 11, 2019 LUMC building 3, V-02-026/028 Peters et al, Chapter 6. slides Richard Gill
February 25, 2019 LUMC building 2, T-00-022 Peters et al, Chapters 1-3. slides Stéphanie van der Pas
December 17, 2018 LUMC building 3, V-03-044 Hernán & Robins, Chapters 15-16. notes Svetlana Belitser
December 10, 2018 Extra materials: Note on Inverse Weighing and Double Robustness. note Aad van der Vaart
December 3, 2018 LUMC building 2, T-00-022 Hernán & Robins, Chapters 11-14. slides Richard Post
November 19, 2018 LUMC building 2, T-00-022 Hernán & Robins, Chapters 1-7. notes Aad van der Vaart

Papers to discuss in the future: