ivreg_tidiers {broom} | R Documentation |
Tidiers for ivreg models
## S3 method for class 'ivreg' tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...) ## S3 method for class 'ivreg' augment(x, data = as.data.frame(stats::model.frame(x)), newdata, ...) ## S3 method for class 'ivreg' glance(x, diagnostics = FALSE, ...)
x |
An "ivreg" 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 |
newdata |
New data to make predictions from (optional) |
diagnostics |
Logical. Return results of diagnostic tests. |
All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.
tidy.ivreg
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 |
and if newdata
is NULL
:
.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 |
Wald test statistic |
p.value |
p-value from the Wald test |
df |
Degrees of freedom used by the coefficients |
sigma |
The square root of the estimated residual variance |
df.residual |
residual degrees of freedom |
If diagnostics
is TRUE
, glance
also returns:
p.value.Sargan |
P value of Sargan test |
p.value.Wu.Hausman |
P value of Wu-Hausman test |
p.value.weakinst |
P value of weak instruments test |
if (require("AER", quietly = TRUE)) { data("CigarettesSW", package = "AER") CigarettesSW$rprice <- with(CigarettesSW, price/cpi) CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi) CigarettesSW$tdiff <- with(CigarettesSW, (taxs - tax)/cpi) ivr <- ivreg(log(packs) ~ log(rprice) + log(rincome) | log(rincome) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995") summary(ivr) tidy(ivr) tidy(ivr, conf.int = TRUE) tidy(ivr, conf.int = TRUE, exponentiate = TRUE) head(augment(ivr)) glance(ivr) }