# Which priors for power simulations (Bayesian GLMMs)

**URL:** <https://discourse.mc-stan.org/t/which-priors-for-power-simulations-bayesian-glmms/33566>\
**Category:** Modeling\
**Tags:** brms, rstan, specification\
**Created:** [December 13, 2023, 9:04am UTC](https://discourse.mc-stan.org/t/which-priors-for-power-simulations-bayesian-glmms/33566 "2023-12-13T09:04:24Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![Bob\_Carpenter](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/bob_carpenter/32/9230_2.png) [@Bob\_Carpenter](https://discourse.mc-stan.org/u/Bob_Carpenter)\
**Post date:** [December 13, 2023, 10:29pm UTC](https://discourse.mc-stan.org/t/which-priors-for-power-simulations-bayesian-glmms/33566/3 "2023-12-13T22:29:27Z")

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> [@stanbeginner](#):
>
> I need to justify the choice of my sample size so I did a design/power analysis by simulating datasets with the expected effects and calculated the power with which the existing effects would be detected in, say, 1,000 simulations.

What does it mean to “detect an existing effect” in a Bayesian setting? This sounds like you’re trying to do some kind of frequentist hypothesis testing.

This has come up before, and last time, [Andrew Gelman recommended a chapter of his book with Jennifer Hill](https://discourse.mc-stan.org/t/bayesian-power-analysis/12363/6). Here’s a [blog post from Andrew](https://statmodeling.stat.columbia.edu/2018/08/24/anyone-claims-80-power-im-skeptical/) the explains why he doesn’t like traditional power analyses along with some constructive suggestions about what you can do.

> [@stanbeginner](#):
>
> So now I would like to ask whether I should even enter any prior assumptions in the model or if I better use uninformed priors for the simulations.

In Bayesian analyses, it’s always best to the use the most informative prior you can justify with your prior knowledge. Sometimes you can get away without doing this when the data is informative enough by itself. And you always want to use all your prior information to simulate, even in a frequentist power calculation.

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