Page 205 - Six Sigma Advanced Tools for Black Belts and Master Black Belts

OTE/SPH
OTE/SPH
August 31, 2006
JWBK119-12
Introduction to the Analysis of Categorical Data
190 2:58 Char Count= 0
1 2 3 1000 2000 3000
4.5
color 3.5
2.5
3
2 spine

1
30
width 25
20
3000
weight
2000
1000
2.5 3.5 4.5 20 25 30
Figure 12.2 Matrix plot to check for multicollinearity due to significant correlations between
explanatory variables.

Table 12.12 Logistic regression table for multiple logistic regression model.
95% CI of
odds ratio
SE p- Odds
Predictors Coefficient Coeff. Z value ratio Lower Upper
Constant −20.332 7.429 −2.74 0.006

Dummy variable
combinations
Color c 11 c 12 c 13
3 1 0 0 1.146 1.244 0.92 0.357 3.15 0.27 36.03
4 0 1 0 0.427 1.440 0.30 0.767 1.53 0.09 25.78
5 0 0 1 −0.841 1.737 −0.48 0.628 0.43 0.01 12.98

Dummy variable
combinations
Spine
Condition c 21 c 22

2 1 0 −0.849 1.413 −0.60 0.548 0.43 0.03 6.83
3 0 1 −1.893 1.191 −1.69 0.112 0.15 0.01 1.56

Width 0.833 0.284 1.15 0.003 2.30 1.32 4.01