Measurement and DAGs

Read before class on Wednesday, February 5, 2020

Required

Measurement

  • 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.
  • “Directed acyclical graphs” in Causal Inference: The Mixtape4

  1. Peter H. Rossi, Mark W. Lipsey, and Gary T. Henry, Evaluation: A Systematic Approach, 8th ed. (Los Angeles: Sage, 2019).↩︎

  2. 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.↩︎

  3. Julian Schuessler and Peter Selb, “Graphical Causal Models for Survey Inference” (Working Paper, SocArXiv, December 17, 2019), doi:10.31235/osf.io/hbg3m.↩︎

  4. Scott Cunningham, Causal Inference: The Mixtape, 2018, https://www.scunning.com/mixtape.html.↩︎

Last updated on April 9, 2020

Edit this page