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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