tidy.betareg | R Documentation |
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 across 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 class 'betareg'
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)
x |
A |
conf.int |
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level |
The confidence level to use for the confidence interval
if |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in
|
The tibble has one row for each term in the regression. The
component
column indicates whether a particular
term was used to model either the "mean"
or "precision"
. Here the
precision is the inverse of the variance, often referred to as phi
.
At least one term will have been used to model the precision phi
.
A tibble::tibble()
with columns:
conf.high |
Upper bound on the confidence interval for the estimate. |
conf.low |
Lower bound on the confidence interval for the estimate. |
estimate |
The estimated value of the regression term. |
p.value |
The two-sided p-value associated with the observed statistic. |
statistic |
The value of a T-statistic to use in a hypothesis that the regression term is non-zero. |
std.error |
The standard error of the regression term. |
term |
The name of the regression term. |
component |
Whether a particular term was used to model the mean or the precision in the regression. See details. |
tidy()
, betareg::betareg()
# load libraries for models and data
library(betareg)
# load dats
data("GasolineYield", package = "betareg")
# fit model
mod <- betareg(yield ~ batch + temp, data = GasolineYield)
mod
# summarize model fit with tidiers
tidy(mod)
tidy(mod, conf.int = TRUE)
tidy(mod, conf.int = TRUE, conf.level = .99)
augment(mod)
glance(mod)
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