broom (version 0.3.7)

plm_tidiers: Tidiers for panel regression linear models

Description

Tidiers for panel regression linear models

Usage

## S3 method for class 'plm':
tidy(x, conf.int = FALSE, conf.level = 0.95,
  exponentiate = FALSE, ...)
## S3 method for class 'plm':
augment(x, data = as.data.frame(model.frame(x)), ...)
## S3 method for class 'plm':
glance(x, ...)

Arguments

x

a "plm" object representing a panel object

conf.int

whether to include a confidence interval

conf.level

confidence level of the interval, used only if conf.int=TRUE

exponentiate

whether to exponentiate the coefficient estimates and confidence intervals

...

extra arguments, not used

data

original dataset

Value

• All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.

  tidy.plm returns a data frame with one row per coefficient, of the same form as tidy.lm.

  augment returns a data frame with one row for each initial observation, adding the columns

• .fitted
  predicted (fitted) values
• .resid
  residuals
• glance returns a one-row data frame with columns
• r.squared
  The percent of variance explained by the model
• adj.r.squared
  r.squared adjusted based on the degrees of freedom
• statistic
  F-statistic
• p.value
  p-value from the F test, describing whether the full regression is significant
• deviance
  deviance
• df.residual
  residual degrees of freedom

See Also

lm_tidiers

Examples

if (require("plm", quietly = TRUE)) {
    data("Produc", package = "plm")
    zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
              data = Produc, index = c("state","year"))

    summary(zz)

    tidy(zz)
    tidy(zz, conf.int = TRUE)
    tidy(zz, conf.int = TRUE, conf.level = .9)

    head(augment(zz))

    glance(zz)
}