tidy.mlogit: Tidying methods for logit models

In broom: Convert Statistical Objects into Tidy Tibbles

Tidying methods for logit models

Description

These methods tidy the coefficients of mnl and nl models generated by the functions of the mlogit package.

Usage

## S3 method for class 'mlogit'
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

Arguments

x	an object returned from mlogit::mlogit().
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.
...	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() methods will warn when supplied an exponentiate argument if it will be ignored. augment() methods will warn when supplied a newdata argument if it will be ignored.

Value

A tibble::tibble() with columns:

conf.high	Upper bound on the confidence interval for the estimate.
conf.low	Lower bound on the confidence interval for the estimate.
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.

See Also

tidy(), mlogit::mlogit()

Other mlogit tidiers: augment.mlogit(), glance.mlogit()

Examples

# load libraries for models and data
library(mlogit)

data("Fishing", package = "mlogit")
Fish <- dfidx(Fishing, varying = 2:9, shape = "wide", choice = "mode")

# fit model
m <- mlogit(mode ~ price + catch | income, data = Fish)

# summarize model fit with tidiers
tidy(m)
augment(m)
glance(m)

broom documentation built on Sept. 30, 2024, 9:29 a.m.