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Toy dataframe with varying levels of multicollinearity

Source: R/data.R
toy.Rd

Dataframe with known relationship between responses and predictors useful to illustrate multicollinearity concepts.

Usage

data(toy)

Format

dataframe with 2000 rows and 5 columns.

Details

Columns:

  • y: response variable generated from a * 0.75 + b * 0.25 + noise.

  • a: most important predictor of y, uncorrelated with b.

  • b: second most important predictor of y, uncorrelated with a.

  • c: generated from a + noise.

  • d: generated from (a + b)/2 + noise.

These are variance inflation factors of the predictors in toy. variable vif b 4.062 d 6.804 c 13.263 a 16.161

See also

Other example_data: vi, vi_predictors, vi_predictors_categorical, vi_predictors_numeric, vi_responses, vi_smol