Glance accepts a `graph_lme`

object and returns a
`tidyr::tibble()`

with exactly one row of model summaries.
The summaries are the square root of the estimated variance of the measurement error, residual
degrees of freedom, AIC, BIC, log-likelihood,
the type of latent model used in the fit and the total number of observations.

## Value

A `tidyr::tibble()`

with exactly one row and columns:

`nobs`

Number of observations used.`sigma`

the square root of the estimated residual variance`logLik`

The log-likelihood of the model.`AIC`

Akaike's Information Criterion for the model.`BIC`

Bayesian Information Criterion for the model.`deviance`

Deviance of the model.`df.residual`

Residual degrees of freedom.`model.type`

Type of latent model fitted.