Here is an example R session that should hopefully help you out

Code:`> #rstandard is a useful function for what you're looking to do. > rstandard function (model, ...) UseMethod("rstandard") <bytecode: 0x0000000028985918> <environment: namespace:stats> > ?rstandard starting httpd help server ... done > head(mtcars) # I'll use the built-in mtcars data for an example mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 > o <- lm(mpg ~ wt, data = mtcars) # build the simple linear regression > o Call: lm(formula = mpg ~ wt, data = mtcars) Coefficients: (Intercept) wt 37.285 -5.344 > summary(o) Call: lm(formula = mpg ~ wt, data = mtcars) Residuals: Min 1Q Median 3Q Max -4.5432 -2.3647 -0.1252 1.4096 6.8727 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 37.2851 1.8776 19.858 < 2e-16 *** wt -5.3445 0.5591 -9.559 1.29e-10 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 3.046 on 30 degrees of freedom Multiple R-squared: 0.7528, Adjusted R-squared: 0.7446 F-statistic: 91.38 on 1 and 30 DF, p-value: 1.294e-10 > rstandard(o) Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive -0.76616765 -0.30743051 -0.70575249 0.43275114 Hornet Sportabout Valiant Duster 360 Merc 240D -0.06681879 -0.23148309 -1.30552216 1.38889709 Merc 230 Merc 280 Merc 280C Merc 450SE 0.78392687 0.10010803 -0.36728706 0.29288651 Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental -0.01683789 -0.63159969 0.42296071 0.76979873 Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla 2.17353314 2.33490215 0.61035691 2.21708271 Toyota Corona Dodge Challenger AMC Javelin Camaro Z28 -0.87964013 -0.99313634 -1.24418015 -1.16279098 Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa 0.82771968 0.12244407 0.05177187 0.42254270 Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E -1.51549710 -0.93086929 -1.07151943 -0.34388215 > rs <- rstandard(o) > rs[abs(rs) > 3] # get any with standardized residual > 3. Looks like there aren't any named numeric(0) > rs[abs(rs) > 2] # so let's get the ones > 2 just for an example Chrysler Imperial Fiat 128 Toyota Corolla 2.173533 2.334902 2.217083`