Tidy summarizes information about the components of the model into a tidy data frame.

## Usage

```
# S3 method for flexsurvreg
tidy(
x,
conf.int = FALSE,
conf.level = 0.95,
pars = "all",
transform = "none",
...
)
```

## Arguments

- x
Output from

`flexsurvreg`

or`flexsurvspline`

, representing a fitted survival model object.- conf.int
Logical. Should confidence intervals be returned? Default is

`FALSE`

.- conf.level
The confidence level to use for the confidence interval if

`conf.int = TRUE`

. Default is`0.95`

.- pars
One of

`"all"`

,`"baseline"`

, or`"coefs"`

for all parameters, baseline distribution parameters, or covariate effects (i.e. regression betas), respectively. Default is`"all"`

.- transform
Character vector of transformations to apply to requested

`pars`

. Default is`"none"`

, which returns`pars`

as-is.Users can specify one or both types of transformations:

`"baseline.real"`

which transforms the baseline distribution parameters to the real number line used for estimation.`"coefs.exp"`

which exponentiates the covariate effects.

See

`Details`

for a more complete explanation.- ...
Not currently used.

## Value

A `tibble`

containing the columns: `term`

, `estimate`

, `std.error`

, `statistic`

, `p.value`

, `conf.low`

, and `conf.high`

, by default.

`statistic`

and `p.value`

are only provided for covariate effects (`NA`

for baseline distribution parameters). These are computed as Wald-type test statistics with p-values from a standard normal distribution.

## Details

`flexsurvreg`

models estimate two types of coefficients, baseline distribution parameters, and covariate effects which act on the baseline distribution. By design, `flexsurvreg`

returns distribution parameters on the same scale as is found in the relevant `d/p/q/r`

functions. Covariate effects are returned on the log-scale, which represents either log-time ratios (accelerated failure time models) or log-hazard ratios for proportional hazard models. By default, `tidy()`

will return baseline distribution parameters on their natural scale and covariate effects on the log-scale.

To transform the baseline distribution parameters to the real-value number line (the scale used for estimation), pass the character argument `"baseline.real"`

to `transform`

. To get time ratios or hazard ratios, pass `"coefs.exp"`

to `transform`

. These transformations may be done together by submitting both arguments as a character vector.

## Examples

```
fitg <- flexsurvreg(formula = Surv(futime, fustat) ~ age, data = ovarian, dist = "gengamma")
tidy(fitg)
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 mu 11.7 1.66 NA NA
#> 2 sigma 0.751 0.244 NA NA
#> 3 Q 0.295 0.912 NA NA
#> 4 age -0.0875 0.0250 -3.50 0.000467
tidy(fitg, pars = "coefs", transform = "coefs.exp")
#> # A tibble: 1 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age 0.916 1.03 -3.50 0.000467
```