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 modelling function. This includes the name of the modelling function or any arguments passed to the modelling 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.

# 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.ergm(). Cautionary note: Mispecified arguments may be silently ignored.

See also

Value

A tibble::tibble() with exactly one row and columns:

AIC

Akaike's Information Criterion for the model.

BIC

Bayesian Information Criterion for the model.

df.null

Needs custom info.

df.residual

Residual degrees of freedom for the model.

iterations

The number of iterations performed before convergence

logLik

The log-likelihood of the model. [stats::logLik()] may be a useful reference.

MCMC.burnin

The burn-in period of the MCMC estimation

MCMC.interval

The interval used during MCMC estimation

MCMC.samplesize

The sample size used during MCMC estimation

null.deviance

Deviance of the null model.

residual.deviance

The residual deviance of the model

independence

Whether the model assumed dyadic independence