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 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
# S3 method for svyglm glance(x, maximal = x, ...)
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
Lumley T, Scott A (2015). AIC and BIC for modelling with complex survey data. Journal of Survey Statistics and Methodology, 3(1). https://doi.org/10.1093/jssam/smu021.
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.
Degrees of freedom used by the null model.
Residual degrees of freedom.
Deviance of the null model.
library(survey)#>#> #>#>#> #>#>#> #>set.seed(123) data(api) # survey design dstrat <- svydesign( id = ~ 1, strata = ~ stype, weights = ~ pw, data = apistrat, fpc = ~ fpc ) # model m <- survey::svyglm( formula = sch.wide ~ ell + meals + mobility, design = dstrat, family = quasibinomial() ) glance(m)#> Error in .svycheck(design): object 'dstrat' not found