I wish it were 100 percent but I agree that it isn’t.

But I wish there were a way to find out ]]>

I am really glad you have joined this discussion,

partly because you really have a global perspective

of the field, including its causal subfield, and partly

because you were the first author ever to include

a causal treatment of Simpson’s paradox in a statistic textbook. Kudos.

But why am I exaggerating?

Isn’t it true that (quoting) “even today, only a small percentage of practicing

statisticians can solve any of the

causal toy problems presented in the Book of Why?”

How many statistics textbooks do you know that have

“causal” in their index?

What percentage of graduating PhD’s in statistics

can use potential outcome notation or graphical

models to solve the Simpson paradox correctly,

as you did in your textbook. Isn’t it “a small

percentage” as I state above?

The “entire subfield of statistics devoted to causal

inference” and the conferences that you mention

are a very recent phenomenon. It is part of the

“Causal Revolution” that I introduce in the Book

of Why, whose modern awakening I attribute to Rubin,

Robins, Greenland and other “statisticians who have

worked on causal inference for many, many years.”

I do not think however that there were “plenty” of such statisticians, but the few that have contributed to the Causal Revolution are notably mentioned in the Book. Please alert me if I have missed any.

I also do not think this amounts to “lumping all statisticians together”. On the contrary, I think it amounts to making a clear distinction between statisticians who have contributed to the Causal Revolution and the great majority of mainstream statisticians who refrained from using causal notation.

I hope I have made it even clearer in the reply that I just sentto Kevin Gray, on kdnuggets.com.

Judea

]]>You are indeed exaggerating. There are statisticians who are unfamiliar with causal inference.

But as you know, there are plenty of statisticians who have worked on causal inference for many, many years.

There is an entire subfield of statistics devoted to causal inference. They even have conferences.

It is misleading to lump all statisticians together.

Larry Wasserman

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