Заметки к главе второй

Заметки к главе второй

And now the algebraic magic: For anyone who takes the trouble to read Wright’s paper, let me warn you that he does not compute his path coefficients in grams per day. He computes them in “standard units” and then converts to grams per day at the end.

Заметки к главе пятой

Заметки к главе пятой

“Cigarette smoking is causally related”: The evidence for women was less clear at that time, primarily because women had smoked much less than men in the early decades of the century.

Заметки к главе восьмой

Заметки к главе восьмой

And Abraham drew near: As before, I have used the King James translation but made small changes to align it more closely with the Hebrew.

The ease and familiarity of such: The 2013 Joint Statistical Meetings dedicated a whole session to the topic “Causal Inference as a Missing Data Problem”—Rubin’s traditional mantra. One provocative paper at that session was titled “What Is Not a Missing Data Problem?” This title sums up my thoughts precisely.

This difference in commitment: Readers who are seeing this distinction for the first time should not feel alone; there are well over 100,000 regression analysts in the United States who are confused by this very issue, together with most authors of statistical textbooks. Things will only change when readers of this book take those authors to task.

Unfortunately, Rubin does not consider: “Pearl’s work is clearly interesting, and many researchers find his arguments that path diagrams are a natural and convenient way to express assumptions about causal structures appealing. In our own work, perhaps influenced by the type of examples arising in social and medical sciences, we have not found this approach to aid the drawing of causal inferences” (Imbens and Rubin 2013, p. 25).

One obstacle I faced was cyclic models: These are models with arrows that form a loop. I have avoided discussing them in this book, but such models are quite important in economics, for example.