rescale.RdPsychologists frequently report data in terms of transformed scales such as “IQ" (mean=100, sd=15, “SAT/GRE" (mean=500, sd=100), “ACT" (mean=18, sd=6), “T-scores" (mean=50, sd=10), or “Stanines" (mean=5, sd=2). The rescale function converts the data to standard scores and then rescales to the specified mean(s) and standard deviation(s).
rescale(x, mean = 100, sd = 15,df=TRUE)A data.frame (default) or matrix of rescaled scores.
See Also scale
T <- rescale(attitude,50,10) #all put on same scale
describe(T)
#> vars n mean sd median trimmed mad min max range skew
#> rating 1 30 50 10 50.71 50.47 8.53 29.76 66.73 36.97 -0.36
#> complaints 2 30 50 10 48.80 50.36 11.14 27.77 67.57 39.81 -0.22
#> privileges 3 30 50 10 48.67 49.69 8.48 31.09 74.41 43.32 0.38
#> learning 4 30 50 10 50.11 50.18 12.63 30.94 65.88 34.93 -0.05
#> raises 5 30 50 10 48.91 49.87 10.69 29.19 72.47 43.28 0.20
#> critical 6 30 50 10 52.76 51.08 7.49 23.96 67.42 43.46 -0.87
#> advance 7 30 50 10 48.12 48.93 8.65 32.57 78.25 45.68 0.85
#> kurtosis se
#> rating -0.77 1.83
#> complaints -0.68 1.83
#> privileges -0.41 1.83
#> learning -1.22 1.83
#> raises -0.60 1.83
#> critical 0.17 1.83
#> advance 0.47 1.83
T1 <- rescale(attitude,seq(0,300,50),seq(10,70,10)) #different means and sigmas
describe(T1)
#> vars n mean sd median trimmed mad min max range skew
#> rating 1 30 0 10 0.71 0.47 8.53 -20.24 16.73 36.97 -0.36
#> complaints 2 30 50 20 47.60 50.73 22.27 5.54 85.15 79.61 -0.22
#> privileges 3 30 100 30 96.00 99.06 25.45 43.28 173.23 129.95 0.38
#> learning 4 30 150 40 150.45 150.74 50.53 73.77 213.50 139.73 -0.05
#> raises 5 30 200 50 194.55 199.36 53.47 95.97 312.37 216.40 0.20
#> critical 6 30 250 60 266.57 256.47 44.95 93.76 354.50 260.74 -0.87
#> advance 7 30 300 70 286.85 292.52 60.52 177.99 497.76 319.77 0.85
#> kurtosis se
#> rating -0.77 1.83
#> complaints -0.68 3.65
#> privileges -0.41 5.48
#> learning -1.22 7.30
#> raises -0.60 9.13
#> critical 0.17 10.95
#> advance 0.47 12.78