Yes, you’re right. Clearly many people who identify as frequentists do hold P(hypothesis) to be meaningful. There are statisticians all over the B/F spectrum as well as not on the spectrum at all. So when I said “frequentists believe …” I could never really be correct because various frequentists believe various different things.
Perhaps we could agree on the following statement: “Probabilities such as P(hypothesis) are never needed to do frequentist analysis.”
For example, the link you gave suggests the following as a characterisation of frequentism:
Goal of Frequentist Inference: Construct procedure with frequency guarantees. (For example, confidence intervals.)
Since frequency guarantees are typically of the form “for each possible true value of theta doing the construction blah on the data will, with probability at least 1-p, yield a result with property blah”. Then since this must hold true for each theta, the distribution for the true value of theta is irrelevant.
I could never really be correct because various frequentists believe various different things.
The interesting questions to me are: (a) “what is the steelman of the frequentist position?” (folks like Larry are useful here), and (b) “are there actually prominent frequentist statisticians who say stupid things?”
By (b) I mean “actually stupid under any reasonable interpretation.”
Clearly many people who identify as frequentists
Quote from the url I linked:
One thing that has harmed statistics — and harmed science — is identity statistics. By this I mean that some
people identify themselves as “Bayesians” or “Frequentists.” Once you attach a label to yourself, you have
painted yourself in a corner.
When I was a student, I took a seminar course from Art Dempster. He was the one who suggested to me that
it was silly to describe a person as being Bayesian of Frequentist. Instead, he suggested that we describe a
particular data analysis as being Bayesian of Frequentist. But we shouldn’t label a person that way.
I think Art’s advice was very wise.
“Keep your identity small”—advice familiar to a LW audience.
Perhaps we could agree on the following statement: “Probabilities such as P(hypothesis) are never needed to do
frequentist analysis.”
I guess you disagree with Larry’s take: B vs F is about goals not methods. I could do Bayesian looking things while having a frequentist interpretation in mind.
In the spirit of collaborative argumentation, can we agree on the following:
We have better things to do than engage in identity politics.
Yes, you’re right. Clearly many people who identify as frequentists do hold P(hypothesis) to be meaningful. There are statisticians all over the B/F spectrum as well as not on the spectrum at all. So when I said “frequentists believe …” I could never really be correct because various frequentists believe various different things.
Perhaps we could agree on the following statement: “Probabilities such as P(hypothesis) are never needed to do frequentist analysis.”
For example, the link you gave suggests the following as a characterisation of frequentism:
Since frequency guarantees are typically of the form “for each possible true value of theta doing the construction blah on the data will, with probability at least 1-p, yield a result with property blah”. Then since this must hold true for each theta, the distribution for the true value of theta is irrelevant.
The interesting questions to me are: (a) “what is the steelman of the frequentist position?” (folks like Larry are useful here), and (b) “are there actually prominent frequentist statisticians who say stupid things?”
By (b) I mean “actually stupid under any reasonable interpretation.”
Quote from the url I linked:
“Keep your identity small”—advice familiar to a LW audience.
I guess you disagree with Larry’s take: B vs F is about goals not methods. I could do Bayesian looking things while having a frequentist interpretation in mind.
In the spirit of collaborative argumentation, can we agree on the following:
We have better things to do than engage in identity politics.