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 aareg tidy(x, ...)
x | An |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
robust.se
is only present when x
was created with
dfbeta = TRUE
.
Other aareg tidiers:
glance.aareg()
Other survival tidiers:
augment.coxph()
,
augment.survreg()
,
glance.aareg()
,
glance.cch()
,
glance.coxph()
,
glance.pyears()
,
glance.survdiff()
,
glance.survexp()
,
glance.survfit()
,
glance.survreg()
,
tidy.cch()
,
tidy.coxph()
,
tidy.pyears()
,
tidy.survdiff()
,
tidy.survexp()
,
tidy.survfit()
,
tidy.survreg()
A tibble::tibble()
with columns:
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
robust version of standard error estimate.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The standard error of the regression term.
The name of the regression term.
z score.
if (requireNamespace("survival", quietly = TRUE)) { library(survival) afit <- aareg( Surv(time, status) ~ age + sex + ph.ecog, data = lung, dfbeta = TRUE ) tidy(afit) } #> # A tibble: 4 × 7 #> term estimate statistic std.error robust.se statistic.z p.value #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 Intercept 0.00505 0.00587 0.00474 0.00477 1.23 0.219 #> 2 age 0.0000401 0.0000715 0.0000723 0.0000700 1.02 0.307 #> 3 sex -0.00316 -0.00403 0.00122 0.00123 -3.28 0.00103 #> 4 ph.ecog 0.00301 0.00367 0.00102 0.00102 3.62 0.000299