Extract and tidy model results from a column of models

Applies a tidying function (default broom.mixed::tidy) to a column of models, returning a tidy data frame with one row per term per model, suitable for downstream summarisation and evaluation in simulation studies.

Usage

extract_model_results(
  models,
  model_col = "model",
  tidy_fun = broom.mixed::tidy,
  .term = NULL
)

Arguments

models

A data frame containing a column of fitted model objects.

model_col

Unquoted column name containing the models. Default is model.

tidy_fun

A tidying function to apply to each model. Default is broom.mixed::tidy. The function must return a data frame with a term column.

.term

Optional string specifying a term to filter after tidying (e.g., "(Intercept)"). If NULL (default), all terms are retained.

Value

A tidy data frame with the original columns of models joined to the tidied model results, typically including columns such as term, estimate, std.error, statistic, and p.value.

Examples

library(dplyr)
library(purrr)
library(broom.mixed)

# Simulate and fit models
sim_models <- tibble(
  id = 1:5,
  model = map(1:5, ~ lm(mpg ~ wt, data = mtcars))
)

# Extract all terms
extract_model_results(sim_models)
#> # A tibble: 10 × 7
#>       id model  term        estimate std.error statistic  p.value
#>    <int> <list> <chr>          <dbl>     <dbl>     <dbl>    <dbl>
#>  1     1 <lm>   (Intercept)    37.3      1.88      19.9  8.24e-19
#>  2     1 <lm>   wt             -5.34     0.559     -9.56 1.29e-10
#>  3     2 <lm>   (Intercept)    37.3      1.88      19.9  8.24e-19
#>  4     2 <lm>   wt             -5.34     0.559     -9.56 1.29e-10
#>  5     3 <lm>   (Intercept)    37.3      1.88      19.9  8.24e-19
#>  6     3 <lm>   wt             -5.34     0.559     -9.56 1.29e-10
#>  7     4 <lm>   (Intercept)    37.3      1.88      19.9  8.24e-19
#>  8     4 <lm>   wt             -5.34     0.559     -9.56 1.29e-10
#>  9     5 <lm>   (Intercept)    37.3      1.88      19.9  8.24e-19
#> 10     5 <lm>   wt             -5.34     0.559     -9.56 1.29e-10

# Extract only the slope term
extract_model_results(sim_models, .term = "wt")
#> # A tibble: 5 × 7
#>      id model  term  estimate std.error statistic  p.value
#>   <int> <list> <chr>    <dbl>     <dbl>     <dbl>    <dbl>
#> 1     1 <lm>   wt       -5.34     0.559     -9.56 1.29e-10
#> 2     2 <lm>   wt       -5.34     0.559     -9.56 1.29e-10
#> 3     3 <lm>   wt       -5.34     0.559     -9.56 1.29e-10
#> 4     4 <lm>   wt       -5.34     0.559     -9.56 1.29e-10
#> 5     5 <lm>   wt       -5.34     0.559     -9.56 1.29e-10