Confidence interval around random effect variances in place of p-value
Thanks. Just to make sure, to declare a statistically NON-significant random effect variance component, the lower bound of the CI must be EXACTLY "0", right? Tha is, for example, a CI like: [.0002, .14] is a statistically significant random-effect variance component but one that perhaps borders a p-value of relatively close to but smaller than .05, right?
On Fri, Apr 2, 2021 at 6:19 PM Ben Bolker <bbolker at gmail.com> wrote:
This seems like a potential can of worms (as indeed are all hypothesis tests of null values on a boundary ...) However, in this case bootstrapping (provided you have resampled appropriately - you may need to do hierarchical bootstrapping ...) seems reasonable, because a null model would give you singular fits (i.e. estimated sd=0) half of the time ... Happy to hear more informed opinions. On 4/2/21 6:55 PM, Jack Solomon wrote:
Dear All,
A colleague of mine suggested that I use the bootstrapped CIs around my
model's random effect variances in place of p-values for them.
But random effect variances (or sds) start from "0". So, to declare a
statistically NON-significant random effect variance component, the
lower bound of the CI must be EXACTLY "0", right?
Thank you very much,
Jack
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