Reading assignments for 256
Evaluation
Each week those of you in 256 will read research papers and write a report describing the research and your evaluation of the work. Each report should be 2-3 pages double-spaced. See below for the list of papers and due dates. You will submit your report on gradescope.
The reports will be graded based on
• Correct identification of the research question
• Accurate summary of the method used in the papers
• Clear summary of the key results
• Thoughtful overall evaluation of the paper (e.g., evaluating the significance, novelty, relevance of the contribution)
Papers
| Reading | Link | Due date |
|---|---|---|
| Bickel et al 1975 Science: Sex Bias in Graduate Admissions: Data from Berkeley | Link | 9/10/24 |
| Holland 1986 JASA Statistics and Causal Inference | Link | 9/17/24 |
| Miratrix 2013 JRSSB Adjusting treatment effect estimates by post-stratication in randomized experiments | Link | 9/24/24 |
| Lin 2013 AOAS: Agnostic notes on regression adjustments to experimental data: Reexamining Freedmans critique | Link | 10/01/24 |
| Li, Ding and Rubin 2018 PNAS Asymptotic theory of rerandomization in treatment-control experiments | Link | 10/08/24 |
| Rosenbaum and Rubin 1983 Biometrika: The central role of the propensity score in observational studies for causal effects | Link | 10/15/24 |
| Lunceford and Davidian 2004 SiM Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study | Link | 10/22/24 |
| Angrist Imbens and Rubin 1996 JASA Identification of causal effects using instrumental variables | Link | 10/29/24 |
| Imbens 2014 StatSci Instrumental Variables: An Econometricians Perspective | Link | 11/5/24 |
| Ding and VanderWeele 2016 Epidemiology: Sensitivity Analysis Without Assumptions | Link | 11/12/24 |
| Pearl 1995 Biometrika Causal diagrams for empirical research | Link | 11/19/24 |
| Frangakis and Rubin 2002 Biometrics Principal stratification in causal inference | Link | 11/26/24 |