Glance at a(n) CMP model object — glance.cmp • mpcmp

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.

Usage

# S3 method for class 'cmp'
glance(x, ...)

Arguments

x: an object class 'cmp' object, obtained from a call to glm.cmp
...: other arguments passed to or from other methods (currently unused).

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.
deviance: (Residual) Deviance of the model.
df.null: Degrees of freedom used by the null model.
df.residual: Residual degrees of freedom.
logLik: The log-likelihood of the model.
nobs: Number of observations used.
null.deviance: Deviance of the null model.

Details

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.

Examples

data(attendance)
M.attendance <- glm.cmp(daysabs ~ gender + math + prog, data = attendance)
glance(M.attendance)
#> # A tibble: 1 × 8
#>   null.deviance df.null logLik   AIC   BIC deviance df.residual  nobs
#>           <dbl>   <dbl>  <dbl> <dbl> <dbl>    <dbl>       <int> <int>
#> 1          456.     313  -864. 1739. 1762.     377.         309   314