Tidy a Weight Model Fit

Posterior summaries of the model terms: the population-level effects and the random-effect standard deviations, plus (when include_random_effects = TRUE) the group-level deviations. By default the per-level deviations are omitted, following the broom.mixed convention.

Usage

# S3 method for class 'kb_fit_weight'
tidy(
  x,
  ...,
  conf_level = 0.95,
  estimate = stats::median,
  sig_fig = 3,
  include_random_effects = FALSE
)

Arguments

x

A kb_fit_weight object.

...

Unused.

conf_level

A number between 0 and 1 giving the compatibility-interval level.

estimate

A function that reduces a numeric vector of posterior draws to a scalar point estimate (e.g. median or mean).

sig_fig

A whole number of significant figures for summary output.

include_random_effects

A flag specifying whether to include the group-level random-effect terms in the output.

Value

A tibble with one row per term and columns term, estimate, lower, upper.

See also

Other generics: augment.kb_fit(), coef.kb_fit(), converged.kb_fit(), fitted.kb_fit_weight(), glance.kb_fit(), kb_stancode(), log_lik.kb_fit(), posterior_epred.kb_fit_weight(), posterior_linpred.kb_fit_weight(), posterior_predict.kb_fit_weight(), predict.kb_fit_weight(), prior_summary.kb_fit(), residuals.kb_fit_weight(), samples(), summary.kb_fit()

Examples

tidy(fit_weight_sim_nereo)
#> # A tibble: 7 × 4
#>   term          estimate   lower  upper
#>   <chr>            <dbl>   <dbl>  <dbl>
#> 1 bWeight        -1.47   -1.66   -1.24 
#> 2 bDiameter       2.5     2.28    2.74 
#> 3 bDiameter2      0.0749 -0.156   0.313
#> 4 sSite           0.27    0.176   0.459
#> 5 sSiteDiameter   0.313   0.169   0.62 
#> 6 sSiteYear       0.0962  0.0521  0.149
#> 7 sWeight         0.161   0.141   0.185