Measurement and DAGs
- The witch trial scene from Monty Python and the Holy Grail
- Chapter 5 in Evaluation: A Systematic Approach.1 This is available on iCollege.
- Chapter 5 in The Effect2
- Julia M. Rohrer, “Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data”3 This will be posted on iCollege.
- Section 2 only (pp. 4–11) from Julian Schuessler and Peter Selb, “Graphical Causal Models for Survey Inference.”4 The PDF is available at SocArXiv.
- Chapters 6 and 7 in The Effect5
DAG example page
- The example page on DAGs shows how to draw and analyze DAGs with both dagitty.net and R + ggdag
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.
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:
Here are all the materials we’ll use in class:
You can use bookdown to create automatic figure, table, and equation numbers. See here for more details:
Make sure you modify the metadata of your document to use bookdown when knitting:
title: whatever output: bookdown::html_document2: number_sections: no
Peter H. Rossi, Mark W. Lipsey, and Gary T. Henry, Evaluation: A Systematic Approach, 8th ed. (Los Angeles: Sage, 2019). ↩︎
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. ↩︎
Huntington-Klein, The Effect. ↩︎