tidy_fits {simpr}

Tidy fits into a tidy tibble

Description

Turn models fit to simulated data (from fit) into a tidy tibble of model estimates (via broom::tidy).

Usage

tidy_fits(obj, ..., .progress = FALSE, .options = furrr_options())

Arguments

obj

a simpr_tibble with fitted models, from fit

...

Additional arguments to the broom::tidy method.

.progress

A logical, for whether or not to print a progress bar for multiprocess, multisession, and multicore plans .

.options

The future specific options to use with the workers when using futures. This must be the result from a call to furrr_options().

Details

This the fifth step of the simulation process: after fitting the model with fit, now tidy the model output for further analysis such as evaluating power. All model objects should be supported by broom::tidy. See apply_fits for applying any arbitrary function to the data, including other tidiers.

The output of this function is quite useful for diagnosing bias, precision, and power. For looking at overall features of the model (e.g., R-squared), use glance_fits.

Value

a tibble with the output of the broom::tidy method applied to each model fit and then bound into a single tibble.

See Also

glance_fits to view overall model statistics (e.g. R-squared), apply_fits to apply an arbitrary function to the fits

Examples

simple_linear_data = specify(a = ~ 2 + rnorm(n),
          b = ~ 5 + 3 * x1 + rnorm(n, 0, sd = 0.5)) %>%
  define(n = 100:101) %>%
  generate(2)

## Can show tidy output for multiple competing models,
compare_degree = simple_linear_data %>%
  fit(linear = ~lm(a ~ b, data = .),
      quadratic = ~lm(a ~ b + I(b^2), data = .)) %>%
  tidy_fits

compare_degree

## Models can be anything supported by broom::tidy.
cor_vs_lm = simple_linear_data %>%
  fit(linear = ~lm(a ~ b, data = .),
      cor = ~ cor.test(.$a, .$b)) %>%
  tidy_fits

cor_vs_lm # has NA for non-matching terms