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

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



an object returned from mlogit::mlogit().

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


The confidence level to use for the confidence interval if = 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.level = 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.

See also


A tibble::tibble() with columns:


Upper bound on the confidence interval for the estimate.


Lower bound on the confidence interval for the estimate.


The estimated value of the regression term.


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


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


The standard error of the regression term.


The name of the regression term.


if (FALSE) { library(mlogit) data("Fishing", package = "mlogit") Fish <- dfidx(Fishing, varying = 2:9, shape = "wide", choice = "mode") m <- mlogit(mode ~ price + catch | income, data = Fish) tidy(m) augment(m) glance(m) }