Dear Colleagues;

        I derived the following equation using MINITAB:

pKi = - 10.9 + 3.77 Tu + 1.89 Tm + 5.55 Av 
          - 6.35 Ap + 37.0 Km - 71.6 Ks

Predictor       Coef       StDev          T        P       VIF
Constant     -10.894       2.798      -3.89    0.005
Tu            3.7654      0.6885       5.47    0.000      37.6
Tm            1.8904      0.4559       4.15    0.003      21.0
Av             5.550       1.100       5.05    0.000    2187.1
Ap            -6.353       1.146      -5.54    0.000    2641.9
Km            37.034       8.609       4.30    0.003      34.7
Ks            -71.61       14.21      -5.04    0.000      85.5

n = 15      SD = 0.5804      R-Sq = 89.6%      F = 11.51


Since the variance inflation factors are so large I generated a
Pearson correlation maxtix:

            Tu      Tm       Av       Ap       Km
Tm        0.261
Av        0.779    0.405
Ap        0.772    0.430    0.999
Km       -0.173    0.525   -0.436   -0.415
Ks       -0.036    0.368   -0.474   -0.463    0.931
 

As you see Ap and Av are colinear.  So I thought to see what
would happen if either of these two variables were omitted from
the equation.  When the data were regressed without Ap I
obtained

pKi = - 5.23 + 1.67 Tu + 0.284 Tm - 0.473 Av + 6.8 Km - 17.6 Ks

Predictor       Coef       StDev          T        P       VIF
Constant      -5.228       5.404      -0.97    0.359
Tu             1.672       1.194       1.40    0.195      26.3
Tm            0.2837      0.7302       0.39    0.707      12.5
Av           -0.4735      0.3596      -1.32    0.220      54.3
Km              6.79       13.82       0.49    0.635      20.8
Ks            -17.63       21.49      -0.82    0.433      45.4

n = 15      S = 1.204       R-Sq = 49.7%      F = 1.78


whereas is Av is omitted I obtain

pKi = - 7.37 + 2.32 Tu + 0.694 Tm - 0.645 Ap + 11.3 Km - 29.9 Ks

Predictor       Coef       StDev          T        P       VIF
Constant      -7.366       5.223      -1.41    0.192
Tu             2.324       1.208       1.92    0.086      31.2
Tm            0.6935      0.7505       0.92    0.380      15.3
Ap           -0.6447      0.3480      -1.85    0.097      65.6
Km             11.25       13.36       0.84    0.421      22.5
Ks            -29.94       22.30      -1.34    0.212      56.6

n = 15      S = 1.119       R-Sq = 56.6%      F = 2.34


My question is: why is there such a decline in the statistical
quality of the regression equation when one of the two colinear
variables (Av or Ap) is omitted??  Since Ap and Av are colinear,
I expected that removing one of them from the 6-variable
equation would have been compensated for by a change in the
coefficient preceding the other, accompanied by only a
negligible change in statistical quality of the 5-variable
equations compared to the 6-variable equation.  Obvious this was
_not_ the case.

        Responders should contact me _directly_ at

[EMAIL PROTECTED]

because I rarely log on to this usegroup.

Thanks in advance to all responders,

S. Shapiro
[EMAIL PROTECTED]



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