11H4:
The data in data(NWOGrants) are outcomes for scientific funding applications for the Netherlands Organization for Scientific Research (NWO) from 2010-2012 (see van der Lee and Ellemers (2015) for data and context). These data have a very similar structure to the UCBAdmit data discussed in the chapter. I want you to consider a similar question: What are the total and indirect causal effects of gender on grant awards? Consider a mediation path (a pipe) through discipline. Draw the corresponding DAG and then use one or more binomial GLMs to answer the question. What is your causal interpretation? If NWO’s goal is to equalize rates of funding between men and women, what type of intervention would be most effective?
Statistical Rethinking Book: shorturl.at/aqLW1
Statistical Rethinking Lecture Series: shorturl.at/gnp48
Statistical Rethinking Github: github.com/rmc...
Make DAGs online: www.dagitty.net/
Pearl's Book on Causality and DAGs: www.amazon.com...
Applebaum's book on Probability and Information: shorturl.at/hrtW6
Stone's book on Information: shorturl.at/aqwNS
My Answers: colab.research...
Full Solution-Videos Playlist: shorturl.at/agFY1
My GitHub Folder: github.com/nic...
Негізгі бет Statistical Rethinking (2nd Ed), Solutions to Problems 11H4
Пікірлер