View source: R/stats-summary-lm-tidiers.R
tidy.summary.lm | 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 'summary.lm'
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 tidy.summary.lm()
method is a potentially useful alternative
to tidy.lm()
. For instance, if users have already converted large lm
objects into their leaner summary.lm
equivalents to conserve memory.
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. |
tidy()
, stats::summary.lm()
Other lm tidiers:
augment.glm()
,
augment.lm()
,
glance.glm()
,
glance.lm()
,
glance.summary.lm()
,
glance.svyglm()
,
tidy.glm()
,
tidy.lm()
,
tidy.lm.beta()
,
tidy.mlm()
# fit model
mod <- lm(mpg ~ wt + qsec, data = mtcars)
modsumm <- summary(mod)
# summarize model fit with tidiers
tidy(mod, conf.int = TRUE)
# equivalent to the above
tidy(modsumm, conf.int = TRUE)
glance(mod)
# mostly the same, except for a few missing columns
glance(modsumm)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.