[CountBayesie]

>The type of analysis being banned is often called a frequentist analysis

I find that there is a trend of associating "bad statistics" with "Frequentists Statistics" which isn't really fair. If you found a statistician trained only in Frequentist methods and asked their opinion on experiment design in psychological research they would likely be just as appalled as any Bayesian.

I'm a big fan of Bayesian methods, but the solutions of "we'll solve the problem of misunderstanding p-values by removing them!" is still a problem of misunderstanding p-values! The misunderstanding is the issue, not the p-value.

[stdbrouw]

The problem is that p-values are begging to be misunderstood, and in fact you cannot use them as a decisionmaking procedure without "misinterpreting" them – after all, you're deciding whether to accept the hypothesis P(HA|D) based on 1-P(D|H0) on the grounds that, while they're not the same, they're proportional. (In that sense the p-value is like the poor man's likelihood ratio.) There's nothing wrong with p-values as a concept, but there's everything wrong with p-values in hypothesis testing. The misunderstanding is baked in.

[im3w1l]

You can update your posterior based on the p-values yourself though. "Well those eggheads may have disproved X, but X is just common sense, so I'm gonna keep believing it anyway. U-until I see more studies confirming the finding I mean."

[rpglover64]

I think the problem is not "if you find a frequentist (as opposed to bayesian) statistician", but "if you find a frequentist (as opposed to bayesian) e.g. biologist".

Non-statisticians have been trained using bad, frequentist methods, and one way of forcing them to retrain is by forcing them to learn new statistical tools to get published.

[colechristensen]

I think what this journal doing is probably a good thing, but only as the lesser of several evils. The truth is something more like... it is easier for soft sciences to abuse frequentist statistics than bayesian. Both have merit, it cannot be argued, but it is simply easier to produce meaningless conclusions with frequentist statistics done wrong.

This situation is so bad that it merits banning frequentist for this journal and I think that's reasonable. This doesn't mean that every journal in every field should, but perhaps it will be a useful temporary measure to improve quality.