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Compute summary statistics for correlation and VIF

Source: R/collinear_stats.R
collinear_stats.Rd

Computes the the minimum, mean, maximum, and quantiles 0.05, 0.25, median (0.5), 0.75, and 0.95 of the correlations and variance inflation factors in a given dataframe. Wraps the functions cor_stats() and vif_stats()

Usage

collinear_stats(df = NULL, predictors = NULL, quiet = FALSE, ...)

Arguments

df

(required; dataframe, tibble, or sf) A dataframe with predictors or the output of cor_df(). Default: NULL.

predictors

(optional; character vector or NULL) Names of the predictors in df. If NULL, all columns except responses and constant/near-zero-variance columns are used. Default: NULL.

quiet

(optional; logical) If FALSE, messages are printed. Default: FALSE.

...

(optional) Internal args (e.g. function_name for validate_arg_function_name, a precomputed correlation matrix m, or cross-validation args for preference_order).

Value

dataframe with columns method (with values "correlation" and "vif"), statistic and value

See also

Other multicollinearity_assessment: cor_clusters(), cor_cramer(), cor_df(), cor_matrix(), cor_stats(), vif(), vif_df(), vif_stats()

Examples

data(
  vi_smol,
  vi_predictors_numeric
  )

## OPTIONAL: parallelization setup
## irrelevant when all predictors are numeric
## only worth it for large data with many categoricals
# future::plan(
#   future::multisession,
#   workers = future::availableCores() - 1
# )

## OPTIONAL: progress bar
# progressr::handlers(global = TRUE)

x <- collinear_stats(
  df = vi_smol,
  predictors = vi_predictors_numeric
)

x
#>         method     statistic     value
#> 1  correlation             n 1081.0000
#> 2  correlation       minimum    0.0011
#> 3  correlation quantile_0.05    0.0426
#> 4  correlation quantile_0.25    0.1817
#> 5  correlation          mean    0.3980
#> 6  correlation        median    0.3610
#> 7  correlation quantile_0.75    0.6184
#> 8  correlation quantile_0.95    0.8264
#> 9  correlation       maximum    0.9893
#> 10         vif             n   47.0000
#> 11         vif       minimum    1.8158
#> 12         vif quantile_0.05    3.7499
#> 13         vif quantile_0.25   58.1814
#> 14         vif          mean  214.5167
#> 15         vif        median  170.1444
#> 16         vif quantile_0.75  354.2920
#> 17         vif quantile_0.95  520.9411
#> 18         vif       maximum  553.2944

## OPTIONAL: disable parallelization
#future::plan(future::sequential)