Measurement and DAGs
Readings
Measurement
- The witch trial scene from Monty Python and the Holy Grail
- Chapter 5 in Evaluation: A Systematic Approach.1 This is available on iCollege.
DAGs
- Julia M. Rohrer, “Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data”2 This will be posted on iCollege.
- Section 2 only (pp. 4–11) from Julian Schuessler and Peter Selb, “Graphical Causal Models for Survey Inference.”3 The PDF is available at SocArXiv.
- Chapter 3, “Directed Acyclic Graphs” in Causal Inference: The Mixtape4
DAG example page
- The example page on DAGs shows how to draw and analyze DAGs with both dagitty.net and R + ggdag
Slides
The slides for today’s lesson are available online as an HTML file. Use the buttons below to open the slides either as an interactive website or as a static PDF (for printing or storing for later). You can also click in the slides below and navigate through them with your left and right arrow keys.
View all slides in new window Download PDF of all slides
Videos
Videos for each section of the lecture are available at this YouTube playlist.
You can also watch the playlist (and skip around to different sections) here:
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Peter H. Rossi, Mark W. Lipsey, and Gary T. Henry, Evaluation: A Systematic Approach, 8th ed. (Los Angeles: Sage, 2019). ↩︎
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Julia M. Rohrer, “Thinking Clearly about Correlations and Causation: Graphical Causal Models for Observational Data,” Advances in Methods and Practices in Psychological Science 1, no. 1 (March 2018): 27–42, doi:10.1177/2515245917745629. ↩︎
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Julian Schuessler and Peter Selb, “Graphical Causal Models for Survey Inference” (Working Paper, SocArXiv, December 17, 2019), doi:10.31235/osf.io/hbg3m. ↩︎
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Scott Cunningham, Causal Inference: The Mixtape (New Haven, CT: Yale University Press, 2021), https://mixtape.scunning.com/. ↩︎