>use bodyfat
SYSTAT Rectangular file bodyfat.SYD,
created Tue Mar 09, 1999 at 13:03:38, contains variables:
 X1           X2           X3           Y
First estimate the full model with x1, x2 & x3.
>mglh

>model y = constant + x1 + x2 + x3

>estimate
 
Dep Var: Y   N: 20   Multiple R: 0.895186   Squared multiple R: 0.801359
 
Adjusted squared multiple R: 0.764113   Standard error of estimate: 2.479981
 
Effect         Coefficient    Std Error     Std Coef Tolerance     t   P(2 Tail)
 
CONSTANT        117.084695    99.782403     0.0        .        1.17340  0.25781
X1                4.334092     3.015511     4.263705  0.001411  1.43727  0.16991
X2               -2.856848     2.582015    -2.928701  0.001772 -1.10644  0.28489
X3               -2.186060     1.595499    -1.561417  0.009560 -1.37014  0.18956
 
                             Analysis of Variance
 
Source             Sum-of-Squares   df  Mean-Square     F-ratio       P
 
Regression            396.984612     3   132.328204   21.515712    0.000007
Residual               98.404888    16     6.150306
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Durbin-Watson D Statistic     2.243
First Order Autocorrelation  -0.168


Second, estimate the reduced model with x1 only
>model y = constant + x1

>estimate
 
Dep Var: Y   N: 20   Multiple R: 0.843265   Squared multiple R: 0.711097
 
Adjusted squared multiple R: 0.695046   Standard error of estimate: 2.819769
 
Effect         Coefficient    Std Error     Std Coef Tolerance     t   P(2 Tail)
 
CONSTANT         -1.496105     3.319235     0.0        .       -0.45074  0.65756
X1                0.857187     0.128781     0.843265  1.000000  6.65617  0.00000
 
                             Analysis of Variance
 
Source             Sum-of-Squares   df  Mean-Square     F-ratio       P
 
Regression            352.269797     1   352.269797   44.304566    0.000003
Residual              143.119703    18     7.951095
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Durbin-Watson D Statistic     1.928
First Order Autocorrelation  -0.006

>splom x1 x2 x3 y/half size=3 den=hist



Last modified 9 March 1999