Glance at a(n) lm objectSource:
Glance accepts a model object and returns a
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
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
of the appropriate type.
# S3 method for aov glance(x, ...)
aovobject, such as those created by
Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in
..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass
conf.lvel = 0.9, all computation will proceed using
conf.level = 0.95. Two exceptions here are:
tidy.aov() now contains the numerator and denominator degrees of
freedom, which were included in the output of
glance.aov() in some
previous versions of the package.
tibble::tibble() with exactly one row and columns:
Akaike's Information Criterion for the model.
Bayesian Information Criterion for the model.
Deviance of the model.
The log-likelihood of the model. [stats::logLik()] may be a useful reference.
Number of observations used.
a <- aov(mpg ~ wt + qsec + disp, mtcars) tidy(a) #> # A tibble: 4 × 6 #> term df sumsq meansq statistic p.value #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 wt 1 848. 848. 121. 1.08e-11 #> 2 qsec 1 82.9 82.9 11.9 1.82e- 3 #> 3 disp 1 0.00102 0.00102 0.000147 9.90e- 1 #> 4 Residuals 28 195. 6.98 NA NA