Prepares the data for dfbetas plot.

ols_prep_dfbeta_data(d, threshold)

Arguments

d

A tibble or data.frame with dfbetas.

threshold

The threshold for outliers.

Examples

model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars) dfb <- dfbetas(model) n <- nrow(dfb) threshold <- 2 / sqrt(n) dbetas <- dfb[, 1] df_data <- data.frame(obs = seq_len(n), dbetas = dbetas) ols_prep_dfbeta_data(df_data, threshold)
#> obs dbetas color fct_color txt #> Mazda RX4 1 -0.2408625040 normal normal NA #> Mazda RX4 Wag 2 -0.0893854682 normal normal NA #> Datsun 710 3 -0.0226714112 normal normal NA #> Hornet 4 Drive 4 0.0165461439 normal normal NA #> Hornet Sportabout 5 -0.0001791988 normal normal NA #> Valiant 6 0.2161392861 normal normal NA #> Duster 360 7 0.0559934442 normal normal NA #> Merc 240D 8 0.0339246041 normal normal NA #> Merc 230 9 0.4484991305 outlier outlier 9 #> Merc 280 10 -0.0178054777 normal normal NA #> Merc 280C 11 -0.0032897727 normal normal NA #> Merc 450SE 12 0.0270335275 normal normal NA #> Merc 450SL 13 -0.0022994410 normal normal NA #> Merc 450SLC 14 0.0663413205 normal normal NA #> Cadillac Fleetwood 15 -0.0010867064 normal normal NA #> Lincoln Continental 16 -0.0129594354 normal normal NA #> Chrysler Imperial 17 -0.0672243472 normal normal NA #> Fiat 128 18 -0.0353581676 normal normal NA #> Honda Civic 19 0.0591178524 normal normal NA #> Toyota Corolla 20 -0.3583658816 outlier outlier 20 #> Toyota Corona 21 0.3763120390 outlier outlier 21 #> Dodge Challenger 22 -0.2073631012 normal normal NA #> AMC Javelin 23 -0.1393390661 normal normal NA #> Camaro Z28 24 -0.0209471589 normal normal NA #> Pontiac Firebird 25 0.0503356537 normal normal NA #> Fiat X1-9 26 -0.0059464066 normal normal NA #> Porsche 914-2 27 0.1174959855 normal normal NA #> Lotus Europa 28 0.1206617098 normal normal NA #> Ford Pantera L 29 -0.0016098012 normal normal NA #> Ferrari Dino 30 -0.0519535108 normal normal NA #> Maserati Bora 31 -0.2994696671 normal normal NA #> Volvo 142E 32 -0.0168421538 normal normal NA