Glance accepts a model object and returns a `tibble::tibble()`

with exactly one row of model summaries. The summaries are typically
goodness of fit measures, p-values for hypothesis tests on residuals,
or model convergence information.

Glance never returns information from the original call to the modeling function. This includes the name of the modeling function or any arguments passed to the modeling function.

Glance does not calculate summary measures. Rather, it farms out these
computations to appropriate methods and gathers the results together.
Sometimes a goodness of fit measure will be undefined. In these cases
the measure will be reported as `NA`

.

Glance returns the same number of columns regardless of whether the
model matrix is rank-deficient or not. If so, entries in columns
that no longer have a well-defined value are filled in with an `NA`

of the appropriate type.

## Usage

```
# S3 method for ergm
glance(x, deviance = FALSE, mcmc = FALSE, ...)
```

## Arguments

- x
An

`ergm`

object returned from a call to`ergm::ergm()`

.- deviance
Logical indicating whether or not to report null and residual deviance for the model, as well as degrees of freedom. Defaults to

`FALSE`

.- mcmc
Logical indicating whether or not to report MCMC interval, burn-in and sample size used to estimate the model. Defaults to

`FALSE`

.- ...
Additional arguments to pass to

`ergm::summary()`

.**Cautionary note**: Misspecified arguments may be silently ignored.

## Value

`glance.ergm`

returns a one-row tibble with the columns

- independence
Whether the model assumed dyadic independence

- iterations
The number of MCMLE iterations performed before convergence

- logLik
If applicable, the log-likelihood associated with the model

- AIC
The Akaike Information Criterion

- BIC
The Bayesian Information Criterion

If `deviance = TRUE`

, and if the model supports it, the
tibble will also contain the columns

- null.deviance
The null deviance of the model

- df.null
The degrees of freedom of the null deviance

- residual.deviance
The residual deviance of the model

- df.residual
The degrees of freedom of the residual deviance

## See also

`glance()`

, `ergm::ergm()`

, `ergm::summary.ergm()`

Other ergm tidiers:
`tidy.ergm()`