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 cross 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, ...)

## Arguments

x |
An `aareg` object returned from `survival::aareg()` . |

... |
Additional arguments. Not used. Needed to match generic
signature only. **Cautionary note:** Misspelled arguments will be
absorbed in `...` , where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass `conf.lvel = 0.9` , all computation will
proceed using `conf.level = 0.95` . Additionally, if you pass
`newdata = my_tibble` to an `augment()` method that does not
accept a `newdata` argument, it will use the default value for
the `data` argument. |

## Details

`robust.se`

is only present when `x`

was created with
`dfbeta = TRUE`

.

## See also

`tidy()`

, `survival::aareg()`

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`

## Value

A `tibble::tibble()`

with columns:

estimateThe estimated value of the regression term.

p.valueThe two-sided p-value associated with the observed statistic.

robust.serobust version of standard error estimate (only when `x` was called with `dfbeta = TRUE`)

statisticThe value of a T-statistic to use in a hypothesis that the regression term is non-zero.

std.errorThe standard error of the regression term.

termThe name of the regression term.

zz score

## Examples

#> # A tibble: 4 x 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