plm_tidiers {broom} | R Documentation |
Tidiers for panel regression linear models
## 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(stats::model.frame(x)), ...) ## S3 method for class 'plm' glance(x, ...)
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
|
exponentiate |
whether to exponentiate the coefficient estimates and confidence intervals |
... |
extra arguments, not used |
data |
original dataset |
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 |
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) }