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.
• Chapter 5 in The Effect²

DAGs

• 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

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

• Introduction
• Abstraction, stretching, and validity
• Causal models
• Paths, doors, and adjustment

Videos

Videos for each section of the lecture are available at this YouTube playlist.

• Introduction
• Abstraction, stretching, and validity
• Causal models
• Paths, doors, and adjustment

You can also watch the playlist (and skip around to different sections) here:

In-class stuff

Here are all the materials we’ll use in class:

• Session 4 FAQ slides (PDF)

You can use bookdown to create automatic figure, table, and equation numbers. See here for more details:

• https://bookdown.org/yihui/rmarkdown-cookbook/figure-number.html
• https://rmd4sci.njtierney.com/figures-tables-captions-.html
• https://rmd4sci.njtierney.com/start.html

Make sure you modify the metadata of your document to use bookdown when knitting:

title: whatever
output: 
  bookdown::html_document2:
    number_sections: no