The Effect: An Introduction to Research Design and Causality Second edition is an excellent
teaching text about research design specifically concerning research that uses observational
data to make a causal inference. It is separated into two halves each with different
approaches to that subject. The first half goes through the concepts of causality with very
little in the way of estimation. It introduces the concept of identification thoroughly and
clearly and discusses it as a process of trying to isolate variation that has a causal
interpretation. Subjects include heavy emphasis on data-generating processes and causal
diagrams. Concepts are demonstrated with a heavy emphasis on graphical intuition and the
question of what we do to data. When we "add a control variable" what does that actually do?
The target audience is practitioners as well as undergraduate and graduate students studying
causal inference in various fields such as statistics econometrics biostatistics the social
sciences and data science. Key Features: Extensive code examples in R Stata and Python
Chapters on heterogeneous treatment effects simulation and power analysis new cutting-edge
methods and uncomfortable ignored assumptions An easy-to-read conversational tone Up-to-date
coverage of methods with fast-moving literatures like difference-in-differences The second
edition features a new chapter on partial identification updated materials methods and
writing throughout and additional materials for help navigating the book or in using the book
in teaching.
