Tidy summarizes information about the components of a model. A model component
might be a single term in a regression, a single hypothesis, a cluster, or a class.
Exactly what tidy considers to be a model component varies cross models but is usually
self-evident. If a model has several distinct types of components, you will need to
specify which components to return. (Description taken from tidyr::tidy help file.)
# S3 method for qgcompfit
tidy(x, conf.level = 1 - x$alpha, exponentiate = FALSE, quick = FALSE, ...)a agcompfit object created by qgcomp().
Real number between 0 and 1 corresponding to nominal percentage/100 of confidence limit (e.g. conf.level=0.95 means 95 per cent confidence intervals). Defaults to 1-alpha level of qgcompfit.
Logical indicating whether or not to exponentiate the the coefficient estimates. This is typical for logistic and multinomial regressions, but a bad idea if there is no log or logit link. Defaults to FALSE.
Logical indiciating if the only the term and estimate columns should be returned. Often useful to avoid time consuming covariance and standard error calculations. Defaults to FALSE.
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. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.