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Extremeness of a case is calculated by the difference between a case's value on the independent variable and the variable's mean value.

Usage

extreme_on_x(lmobject = NULL, ind_var = NULL)

Arguments

lmobject

Object generated with lm

ind_var

Independent variable for which extremeness values should be calculated. Has to be entered as a character.

Value

A dataframe with

- all variables in the linear model,

- absolute extremeness (absolute value of difference between variable score and mean value of variable),

- extremeness (difference between variable score and mean value of variable), which can be useful when the direction of extremeness is relevant.

The rows are ordered in decreasing order of the absolute extreme values.

Details

Calculating the absolute value of the difference between the cases' values and the variable's mean value is proposed by Seawright, Jason (2016): The Case for Selecting Cases That Are Deviant or Extreme on the Independent Variable. Sociological Methods & Research 45 (3): 493-525. (doi:10.1177/0049124116643556 )

Examples

df <- lm(mpg ~ disp + wt, data = mtcars)
extreme_on_x(df, "wt")
#>                      mpg  disp    wt abs. extremeness extremeness
#> Lincoln Continental 10.4 460.0 5.424          2.20675     2.20675
#> Chrysler Imperial   14.7 440.0 5.345          2.12775     2.12775
#> Cadillac Fleetwood  10.4 472.0 5.250          2.03275     2.03275
#> Lotus Europa        30.4  95.1 1.513          1.70425    -1.70425
#> Honda Civic         30.4  75.7 1.615          1.60225    -1.60225
#> Toyota Corolla      33.9  71.1 1.835          1.38225    -1.38225
#> Fiat X1-9           27.3  79.0 1.935          1.28225    -1.28225
#> Porsche 914-2       26.0 120.3 2.140          1.07725    -1.07725
#> Fiat 128            32.4  78.7 2.200          1.01725    -1.01725
#> Datsun 710          22.8 108.0 2.320          0.89725    -0.89725
#> Merc 450SE          16.4 275.8 4.070          0.85275     0.85275
#> Toyota Corona       21.5 120.1 2.465          0.75225    -0.75225
#> Pontiac Firebird    19.2 400.0 3.845          0.62775     0.62775
#> Camaro Z28          13.3 350.0 3.840          0.62275     0.62275
#> Mazda RX4           21.0 160.0 2.620          0.59725    -0.59725
#> Merc 450SLC         15.2 275.8 3.780          0.56275     0.56275
#> Merc 450SL          17.3 275.8 3.730          0.51275     0.51275
#> Ferrari Dino        19.7 145.0 2.770          0.44725    -0.44725
#> Volvo 142E          21.4 121.0 2.780          0.43725    -0.43725
#> Duster 360          14.3 360.0 3.570          0.35275     0.35275
#> Maserati Bora       15.0 301.0 3.570          0.35275     0.35275
#> Mazda RX4 Wag       21.0 160.0 2.875          0.34225    -0.34225
#> Dodge Challenger    15.5 318.0 3.520          0.30275     0.30275
#> Valiant             18.1 225.0 3.460          0.24275     0.24275
#> Hornet Sportabout   18.7 360.0 3.440          0.22275     0.22275
#> Merc 280            19.2 167.6 3.440          0.22275     0.22275
#> Merc 280C           17.8 167.6 3.440          0.22275     0.22275
#> AMC Javelin         15.2 304.0 3.435          0.21775     0.21775
#> Merc 230            22.8 140.8 3.150          0.06725    -0.06725
#> Ford Pantera L      15.8 351.0 3.170          0.04725    -0.04725
#> Merc 240D           24.4 146.7 3.190          0.02725    -0.02725
#> Hornet 4 Drive      21.4 258.0 3.215          0.00225    -0.00225