Chapter Contents |
Previous |
Next |
Fit Analyses |
After scaling (X'X) to correlation form,
Belsley, Kuh, and Welsch (1980) construct the condition
indices as the square roots of the ratio of the largest
eigenvalue to each individual eigenvalue,
d1 / dj,
j = 1, 2, ... , p.
The condition number of the X matrix
is defined as the largest condition index,
d1 / dp.
When this number is large, the
data are said to be ill conditioned.
A condition index of 30 to 100 indicates
moderate to strong collinearity.
For each variable, the proportion of the variance
of its estimate accounted for by each component
dj can be evaluated.
A collinearity problem occurs when a component
associated with a high condition index contributes
strongly to the variance of two or more variables.
Thus, for a high condition index (>30), the corresponding row
should be examined to see which variables have high values.
Those would indicate near-linear dependence.
Chapter Contents |
Previous |
Next |
Top |
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.