I have trial level data from a study in which participants responded to a series of stimuli. I have a predictor of interest. For the sake of this example, let’s call it the size of the stimuli.

There is a null effect of size on both reaction time and accuracy. So I was asked to compute the Bayes Factor for that predictor.

I don’t have a clear way to choose an informed prior, and so I am computing the Bayes Factor across a range of priors. I am using the package rstanarm in R for this.

In the analyses of reaction time, I compute the Bayes Factor for size across a range of priors. In particular, normal distributions centred at 0 with sds ranging from 0.10 to 5. I do this using the `stan_lmer()`

function.

I want to do the same for accuracy, analyzed using `stan_glmer(family = "binomial")`

. My question is if it makes sense to use the same range of priors as I did in the analysis of reaction time?