Preface to First Edition - lib

INTRODUCTION 163Table 9.1:bodyfat data (continued).DEXfat age waistcirc hipcirc elbowbreadth kneebreadth45.92 63 116.8 132.0 6.1 9.842.23 62 112.0 127.0 7.2 11.047.48 42 115.0 128.5 6.6 10.060.72 41 115.0 125.0 7.3 11.832.74 67 89.8 109.0 6.3 9.627.04 67 82.2 103.6 7.2 9.221.07 43 75.0 99.3 6.0 8.437.49 54 98.0 109.5 7.0 10.038.08 49 105.0 116.3 7.0 9.540.83 25 89.5 122.0 6.5 10.018.51 26 87.8 94.0 6.6 9.026.36 33 79.2 107.7 6.5 9.020.08 36 80.0 95.0 6.4 9.043.71 38 105.5 122.5 6.6 10.031.61 26 95.0 109.0 6.7 9.528.98 52 81.5 102.3 6.4 9.218.62 29 71.0 92.0 6.4 8.518.64 31 68.0 93.0 5.7 7.213.70 19 68.0 88.0 6.5 8.214.88 35 68.5 94.5 6.5 8.816.46 27 75.0 95.0 6.4 9.111.21 40 66.6 92.2 6.1 8.511.21 53 66.6 92.2 6.1 8.514.18 31 69.7 93.2 6.2 8.120.84 27 66.5 100.0 6.5 8.519.00 52 76.5 103.0 7.4 8.518.07 59 71.0 88.3 5.7 8.9A second set of data that will also be used in this chapter involves the investigationreported in Mardin et al. (2003) of whether laser scanner images ofthe eye background can be used to classify a patient’s eye as suffering fromglaucoma or not. Glaucoma is a neuro-degenerative disease of the optic nerveand is one of the major reasons for blindness in elderly people. For 196 people,98 patients suffering glaucoma and 98 controls which have been matched byage and gender, 62 numeric variables derived from the laser scanning imagesare available. The data are available as GlaucomaM from package ipred (Peterset al., 2002). The variables describe the morphology of the optic nerve head,i.e., measures of volumes and areas in certain regions of the eye background.Those regions have been manually outlined by a physician. Our aim is to constructa prediction model which is able to decide whether an eye is affectedby glaucomateous changes based on the laser image data.© 2010 by Taylor and Francis Group, LLC