How can I get the standard error of the standard deviation of the random intercept in a cumulative linear mixed model using "ordinal" package in R?

# A tibble: 7,500 × 4 cluster cluster_size x ordinal_y <int> <int> <dbl> <fct> 1 1 1 2.57 4 2 1 2 3.59 4 3 1 3 2.51 1 4 1 4 3.80 3 5 1 5 2.84 4 6 1 6 2.59 1 

This is my data. I fitted the following model on this data.

mod1 <- ordinal::clmm(ordinal_y ~ x + (1 | cluster), data = dat1, link = "logit") 

These are the model result.

mod1 Cumulative Link Mixed Model fitted with the Laplace approximation formula: ordinal_y ~ x + (1 | cluster) data: dat1 link threshold nobs logLik AIC niter max.grad logit flexible 7500 -7634.28 15278.56 364(1095) 1.45e-02 Random effects: Groups Name Variance Std.Dev. cluster (Intercept) 0.2913 0.5398 Number of groups: cluster 150 Coefficients: x 0.7586 Thresholds: 1|2 2|3 3|4 0.5955 1.1092 1.6108 

The standard deviation of the random error, I get by mod1$ST is as follows

$cluster (Intercept) (Intercept) 0.5397603 

I want the standard error of the of the standard deviation I got for random intercept. How can I get this?

I tried the function vcov(mod1) and got the follwoing the result.

vcov(mod1) 1|2 2|3 3|4 x ST1 1|2 0.0038323677 0.0037161142 0.0036710729 0.0006564625 0.0001370114 2|3 0.0037161142 0.0039511707 0.0038837447 0.0007111263 0.0002270493 3|4 0.0036710729 0.0038837447 0.0041400738 0.0007645963 0.0003178104 x 0.0006564625 0.0007111263 0.0007645963 0.0003864496 0.0001702783 ST1 0.0001370114 0.0002270493 0.0003178104 0.0001702783 0.0058518536 

Is ST1*St1 the result I am expecting?