you can peak every time if you do it Bayes — 100% no p-hacking guaranteed 

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Replying to @o_guest @timtriche and
You can peek, but there is a multiple comparisons problem, because of high probability data will be misleading.
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Replying to @o_guest @timtriche and
If you use a BF > e.g., 3 to conclude there is an effect, you will have a multiple comparison issue.
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Replying to @lakens @timtriche and
Do you even have to use BFs? Aren't they just something p value fanatics crave regardless of usefulness?
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Replying to @o_guest @timtriche and
Which Bayesian approach did you have in mind? And why would multiple comparisons not be a problem?
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Replying to @lakens @timtriche and
I'm hoping you can explain your thoughts more to me — here's someth on mult comps, I'm sure you're familiar w/ it: http://www.stat.columbia.edu/~gelman/research/published/multiple2f.pdf …
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Replying to @o_guest @timtriche and
Or more formally: if you never test a hypothesis, you never make an error. Only estimate. It's a solution, but not in my field
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You're saying Gelman never tests hypotheses?
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