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, ...)



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.


robust.se is only present when x was created with dfbeta = TRUE.

See also


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


library(survival) afit <- aareg( Surv(time, status) ~ age + sex + ph.ecog, data = lung, dfbeta = TRUE ) tidy(afit)
#> # 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