This is the wiki page for the McGill Causal Inference reading group. We are a group of professors, post-docs and students who are interested in causal inference methodology and applications. We are a multi-disciplinary group with people coming from biostatistics, computer science, epidemiology, math and statistics.

The paper for August 27th. Discussion led by Russ.

• van der Laan, Mark J. and Rubin, Daniel (2006) “Targeted Maximum Likelihood Learning,” The International Journal of Biostatistics: Vol. 2 : Iss. 1, Article 11.

The paper for August 6th. Discussion led by Ben.

• Rosenblum, Michael and van der Laan, Mark J. (2010) “Targeted Maximum Likelihood Estimation of the Parameter of a Marginal Structural Model,” The International Journal of Biostatistics: Vol. 6 : Iss. 2, Article 19.

The paper for May 7th. Discussion led by Yongling

• Muthén and Brown. Estimating drug effects in the presence of placebo response: Causal inference using growth mixture modeling. Statistics in Medicine, 2009 28:27 pp. 3363-3385

The paper for April 23rd. Discussion led by Robert

• Frangakis CE, Rubin DB. Principal stratification in causal inference. Biometrics. 2002 Mar;58(1):21-9.

April 9th. Cancelled due to a seminar of interest to the reading group, paper discussion postponed.

The paper for March 26th. Discussion led by Jay

• Nandi A, Glass TA, Cole SR, Chu H, Galea S, Celentano DD, Kirk GD, Vlahov D, Latimer WW, Mehta SH. Neighborhood poverty and injection cessation in a sample of injection drug users. Am J Epidemiol. 2010 Feb 15;171(4):391-8.

The paper for March 12th. Discussion led by Mireille

• “Marginal structural models for estimating the effect of highly active antiretroviral therapy initiation on CD4 cell count.” Cole SR, Hernán MA, Margolick JB, Cohen MH, Robins JM. Am J Epidemiol. 2005 Sep 1;162(5):471-8.

The paper for Feb 26th. Discussion led by Ashkan.

• “For objective causal inference, design trumps analysis”, Donald B. Rubin. Annals of Applied Statistics, 2008; 2(3): 808-840

Paper for Feb 12th. Discussion led by Russ.

• “Variable selection for propensity score models”, Brookhart MA, Schneeweiss S, Rothman KJ, Glynn RJ, Avorn J, Stürmer T. American Journal of Epidemiology, 2006 Jun 15;163(12):1149-56.

Paper for Jan 29th. Discussion led by Susan.

• “Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology”, Miguel A. Hernan, Sonia Hernandez-Diaz, Martha M.Werler, and Allen A. Mitchell. American Journal of Epidemiology, 2002 Vol 155, No 2, pp. 176-184.

Paper for Jan 15th. Discussion lead by Micheal.

• ”Four Types of Effect Modification A Classification Based on Directed Acyclic Graphs” Tyler J. VanderWeele and James M. Robins, Epidemiology, 2007 Sep 18. vol 5, pp.569-72

Paper for December 11th. Discussion lead by Russ.

• “Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data,” (with discussion) Joseph D. Y. Kang and Joseph L. Schafer, Statistical Science 2007, Vol. 22, No. 4, 523–539

Paper for November 27th. Discussion lead by Genevieve.

• “Logistic Regression With Incomplete Covariate Data in Complex Survey Sampling Aplication of Reweighted Estimating Equations,” Charity G. Moore,Stuart R. Lipsitz, Cheryl L. Addy, James R. Hussey, Garrett Fitzmaurice, and Sundar Natarajand. Epidemiology, Volume 20, Number 3, May 2009

Paper for 13th November

• “Identification of Causal Effects Using Instrumental Variables,” (Angrist, Imbens and Rubin), JASA Applications invited paper, with comments and authors' rejoinder, Journal of the American Statistical Association, June 1996. Angrist et al. 1996

• My slides here 2 x 1 format
• Greenland (2000) paper here

four_types_of_effect_modification_a_classification_based_on_directed_acyclic_graphs.pdf - Ordered List Item