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11.4 LOGISTIC REGRESSION 565
REACTIVE AGE VERBALIQ STIM AGEABUSE CTQ TOTALHOS
2.3 14 73 0 2 8 9
3.0 12 112 0 0 15 9
1.3 15 102 0 1 1 5
3.0 16 78 1 1 26 8
2.3 9 95 1 0 23 10
1.0 15 124 0 3 0 11
3.0 17 73 0 1 1 10
3.3 11 105 0 0 23 5
4.0 11 89 0 0 27 8
1.7 9 88 0 1 2 8
2.3 16 96 0 1 5 7
4.7 15 76 1 1 17 9
1.7 16 87 0 2 0 4
1.7 15 90 0 1 10 12
4.0 12 76 0 0 22 10
5.0 12 83 1 1 19 7
4.3 10 88 1 0 10 5
5.0 9 98 1 0 8 9
3.7 12 100 0 0 6 4
3.3 14 80 0 1 3 10
2.3 16 84 0 1 3 9
1.0 17 117 0 2 1 9
1.7 12 145 1 0 0 5
3.7 12 123 0 0 1 3
2.0 16 94 0 2 6 6
3.7 17 70 0 1 11 13
4.3 14 113 0 0 8 8
2.0 12 123 1 0 2 8
3.0 7 107 0 0 11 9
3.7 12 78 1 0 15 11
4.3 14 73 0 1 2 8
2.3 18 91 0 3 8 10
4.7 12 91 0 0 6 9
3.7 15 111 0 0 2 9
1.3 15 71 0 1 20 10
3.7 7 102 0 0 14 9
1.7 9 89 0 0 24 6
Source: Daniel F. Connor, M.D. and Lang Lin. Used with permission.
11.4 LOGISTIC REGRESSION
Up to now our discussion of regression analysis has been limited to those situations
in which the dependent variable is a continuous variable such as weight, blood pressure,
or plasma levels of some hormone. Much research in the health sciences field