socrateslab / causal101

Causal Inference 101 Slides

Causal Inference 101

• Slides https://nbviewer.org/format/slides/github/socrateslab/causal101/blob/main/causal101.ipynb#/
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• Notebook https://nbviewer.org/github/socrateslab/causal101/blob/main/causal101.ipynb Cancel changes

Reading list in Week 1

Reading list:

• Lipsky, A. M., & Greenland, S. (2022). Causal directed acyclic graphs. JAMA, 327(11), 1083-1084.
• Rohrer, J. M., Hünermund, P., Arslan, R. C., & Elson, M. (2022). That’sa lot to PROCESS! Pitfalls of popular path models. Advances in Methods and Practices in Psychological Science, 5(2), 25152459221095827.
• Williams, T. C., Bach, C. C., Matthiesen, N. B., Henriksen, T. B., & Gagliardi, L. (2018). Directed acyclic graphs: a tool for causal studies in paediatrics. Pediatric research, 84(4), 487-493.
• Wysocki, A. C., Lawson, K. M., & Rhemtulla, M. (2022). Statistical control requires causal justification. Advances in Methods and Practices in Psychological Science, 5(2), 25152459221095823.

Examples:

• Abraido-Lanza, A. F., Dohrenwend, B. P., Ng-Mak, D. S., & Turner, J. B. (1999). The Latino mortality paradox: a test of the" salmon bias" and healthy migrant hypotheses. American journal of public health, 89(10), 1543-1548.
• Agnew, R. (2013). When criminal coping is likely: An extension of general strain theory. Deviant Behavior, 34(8), 653-670.
• Moffitt, & Terrie, E. . (1993). Adolescence-limited and life-course-persistent antisocial behavior: a developmental taxonomy. Psychological Review, 100(4), 674-701.