Measurement and DAGs

Content for the week of Monday, September 14, 2020–Friday, September 18, 2020

Readings

Measurement

DAGs

  • Julia M. Rohrer, “Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data” 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. This will be posted on iCollege.
  • Section 2 only (pp. 4–11) from Julian Schuessler and Peter Selb, “Graphical Causal Models for Survey Inference.” Julian Schuessler and Peter Selb, “Graphical Causal Models for Survey Inference,” Working Paper (SocArXiv, December 17, 2019), doi:10.31235/osf.io/hbg3m. The PDF is available at SocArXiv.
  • “Directed acyclical graphs” in Causal Inference: The Mixtape Scott Cunningham, Causal Inference: The Mixtape, 2018, https://www.scunning.com/mixtape.html.

DAG example page

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.

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Fun fact: If you type ? (or shift + /) while going through the slides, you can see a list of special slide-specific commands.

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: