broom (version 0.7.8)

tidy.gam: Tidy a(n) gam object

Description

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 across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

# S3 method for gam
tidy(
  x,
  parametric = FALSE,
  conf.int = FALSE,
  conf.level = 0.95,
  exponentiate = FALSE,
  ...
)

Arguments

x

A gam object returned from a call to mgcv::gam().

parametric

Logical indicating if parametric or smooth terms should be tidied. Defaults to FALSE, meaning that smooth terms are tidied by default.

conf.int

Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to FALSE.

conf.level

The confidence level to use for the confidence interval if conf.int = TRUE. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.

exponentiate

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.

...

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.

Value

A tibble::tibble() with columns:

estimate

The estimated value of the regression term.

p.value

The two-sided p-value associated with the observed statistic.

statistic

The value of a T-statistic to use in a hypothesis that the regression term is non-zero.

std.error

The standard error of the regression term.

term

The name of the regression term.

edf

The effective degrees of freedom. Only reported when `parametric = FALSE`

ref.df

The reference degrees of freedom. Only reported when `parametric = FALSE`

Details

When parametric = FALSE return columns edf and ref.df rather than estimate and std.error.

See Also

tidy(), mgcv::gam()

Other mgcv tidiers: glance.gam()

Examples

# NOT RUN {
g <- mgcv::gam(mpg ~ s(hp) + am + qsec, data = mtcars)

tidy(g)
tidy(g, parametric = TRUE)
glance(g)
augment(g)
# }