Tidy a(n) plm object

Source: R/plm-tidiers.R

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.

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

Arguments

x

A plm objected returned by plm::plm().
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 one row for each term in the regression. The tibble has columns:

term

The name of the regression term.

estimate

The estimated value of the regression term.

std.error

The standard error of the regression term.

statistic

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

p.value

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

conf.low

The low end of a confidence interval for the regression term. Included only if conf.int = TRUE.

conf.high

The high end of a confidence interval for the regression term. Included only if conf.int = TRUE.

See also

tidy(), plm::plm(), tidy.lm()

Other plm tidiers: augment.plm, glance.plm

Examples


library(plm)
#> Error in library(plm): there is no package called ‘plm’

data("Produc", package = "plm")
#> Error in find.package(package, lib.loc, verbose = verbose): there is no package called ‘plm’
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
          data = Produc, index = c("state","year"))
#> Error in plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,     index = c("state", "year")): could not find function "plm"

summary(zz)
#> Error in summary(zz): object 'zz' not found

tidy(zz)
#> Error in tidy(zz): object 'zz' not found
tidy(zz, conf.int = TRUE)
#> Error in tidy(zz, conf.int = TRUE): object 'zz' not found
tidy(zz, conf.int = TRUE, conf.level = .9)
#> Error in tidy(zz, conf.int = TRUE, conf.level = 0.9): object 'zz' not found

augment(zz)
#> Error in augment(zz): object 'zz' not found
glance(zz)
#> Error in glance(zz): object 'zz' not found