Tidy the parameters of a fitted freqTLS model

tidy_parameters() returns a broom-style tibble of the natural-scale parameter estimates with optional Wald confidence intervals. The intervals are computed on the internal (unconstrained / link) scale as estimate +/- z * std.error and then back-transformed to the natural scale, so they respect each parameter's bounds (for example z > 0, 0 < low < up) and are equivariant under the link. For CTmax (identity link) this is the usual symmetric Wald interval.

Usage

tidy_parameters(
  fit,
  conf.int = TRUE,
  conf.level = 0.95,
  method = c("wald", "profile")
)

Arguments

fit

A profile_tls fit from fit_tls().

conf.int

Logical; include conf.low / conf.high columns (default TRUE).

conf.level

Confidence level for the interval (default 0.95).

method

Either "wald" (default) or "profile".

Value

A tibble with one row per natural-scale parameter and the columns parameter, group, estimate, std.error, conf.low, conf.high, interval_type, and scale. scale is the link on which the interval was constructed ("identity", "log", or "logit"); interval_type is "wald" or "profile".

Details

With method = "profile" the intervals are profile-likelihood confidence intervals (see confint.profile_tls()); with method = "wald" (default) they are the back-transformed internal-link Wald intervals. The returned shape is identical; only interval_type and the interval values differ. A profile that does not close returns NA on the open side (never a fabricated bound).

Examples

d <- simulate_tls(family = "binomial", CTmax = 36, z = 4, seed = 1)
fit <- fit_tls(d, y = survived, n = total, time = duration, temp = temp,
               family = "binomial", tref = 1)
tidy_parameters(fit)
#> # A tibble: 5 × 8
#>   parameter group estimate std.error conf.low conf.high interval_type scale   
#>   <chr>     <chr>    <dbl>     <dbl>    <dbl>     <dbl> <chr>         <chr>   
#> 1 low       NA      0.0199   0.00552   0.0115    0.0345 wald          logit   
#> 2 up        NA      0.977    0.00797   0.962     0.993  wald          identity
#> 3 k         NA      4.89     0.413     4.14      5.78   wald          log     
#> 4 CTmax     all    35.9      0.105    35.7      36.1    wald          identity
#> 5 z         all     4.00     0.191     3.64      4.40   wald          log     
tidy_parameters(fit, method = "profile")
#> "up" is profiled with the delta-method Wald interval.
#> ℹ The profile path is not yet wired for the disjoint-bounds "up" coordinate
#>   `beta_up`; use the reported Wald interval or request a bootstrap interval.
#> # A tibble: 5 × 8
#>   parameter group estimate std.error conf.low conf.high interval_type scale   
#>   <chr>     <chr>    <dbl>     <dbl>    <dbl>     <dbl> <chr>         <chr>   
#> 1 low       NA      0.0199   0.00552   0.0191    0.0631 profile       logit   
#> 2 up        NA      0.977    0.00797   0.962     0.993  wald          identity
#> 3 k         NA      4.89     0.413     4.13      5.78   profile       log     
#> 4 CTmax     all    35.9      0.105    35.7      36.1    profile       identity
#> 5 z         all     4.00     0.191     3.62      4.38   profile       log