You claim that medical researchers are doing logical inference incorrectly. But they are in fact doing statistical inference and arguing inductively.
Jaynes argued that probability theory was an extension of logic, so this seems like quite a quibbling point.
Statistical inference and inductive arguments belong in a Bayesian framework. You are making a straw man by translating them into a deductive framework.
They do, but did the paper he dealt with write within a Bayesian framework? I didn’t read it, but it sounded like standard “let’s test a null hypothesis” fare.
No. Mattes and Gittelman’s finding is stronger than your rephrasing—your rephrasing omits evidence useful for Bayesian reasoners.
Which is not a valid objection to Phil’s analysis if Mattes and Gittelman weren’t doing a Bayesian analysis in the first place. Were they? I’ll apologize for not checking myself if I’m wrong, but right now my priors are extremely low so I don’t see value in expending the effort to verify.
Their paper should be seen in a Bayesian framework
If they did their calculations in a Bayesian framework. Did they?
hey do, but did the paper he dealt with write within a Bayesian framework? I didn’t read it, but it sounded like standard “let’s test a null hypothesis” fare.
You don’t just ignore evidence because someone used a hypothesis test instead of your favorite Bayesian method. P(null | p value) != P(null)
I ignore evidence when the evidence doesn’t relate to the point of contention.
Phil criticized a bit of paper, noting that the statistical analysis involved did not justify the conclusion made. The conclusion did not follow the analysis. Phil was correct in that criticism.
It’s just not an argument against Phil that someone might take some of the data in the paper and do a Bayesian analysis that the authors did not do.
It’s just not an argument against Phil that someone might take some of the data in the paper and do a Bayesian analysis that the authors did not do.
That’s not what I’m saying. I’m saying that what the authors did do IS evidence against the hypothesis in question. Evidence against a homogenous response is evidence against any response (it makes some response less likely)
Are you saying the measurements they took make their final claim more likely, or that their analysis of the data is correct and justifies their claim?
Yes, if you arrange things moderately rationally, evidence against a homogenous response is evidence against any response, but much less so. I think Phil agrees with that too, and is objecting to a conclusion based on much less so evidence pretending to have much more justification than it does.
Ok, yeah, translating what the researchers did into a Bayesian framework isn’t quite right either. Phil should have translated what they did into a frequentist framework—i.e. he still straw manned them. See my comment here.
Jaynes argued that probability theory was an extension of logic, so this seems like quite a quibbling point.
They do, but did the paper he dealt with write within a Bayesian framework? I didn’t read it, but it sounded like standard “let’s test a null hypothesis” fare.
Which is not a valid objection to Phil’s analysis if Mattes and Gittelman weren’t doing a Bayesian analysis in the first place. Were they? I’ll apologize for not checking myself if I’m wrong, but right now my priors are extremely low so I don’t see value in expending the effort to verify.
If they did their calculations in a Bayesian framework. Did they?
You don’t just ignore evidence because someone used a hypothesis test instead of your favorite Bayesian method. P(null | p value) != P(null)
I ignore evidence when the evidence doesn’t relate to the point of contention.
Phil criticized a bit of paper, noting that the statistical analysis involved did not justify the conclusion made. The conclusion did not follow the analysis. Phil was correct in that criticism.
It’s just not an argument against Phil that someone might take some of the data in the paper and do a Bayesian analysis that the authors did not do.
That’s not what I’m saying. I’m saying that what the authors did do IS evidence against the hypothesis in question. Evidence against a homogenous response is evidence against any response (it makes some response less likely)
What they did do?
Are you saying the measurements they took make their final claim more likely, or that their analysis of the data is correct and justifies their claim?
Yes, if you arrange things moderately rationally, evidence against a homogenous response is evidence against any response, but much less so. I think Phil agrees with that too, and is objecting to a conclusion based on much less so evidence pretending to have much more justification than it does.
Ok, yeah, translating what the researchers did into a Bayesian framework isn’t quite right either. Phil should have translated what they did into a frequentist framework—i.e. he still straw manned them. See my comment here.
I know that. That’s not the point. They claimed to have proven something they did not prove. They did not present this claim in a Bayesian framework.