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楼主

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发表于 2009-6-14 13:19:06
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【求助】关于SAS分析二次回归正交旋转设计的试验实例
此试验是一个四因子(1/2实施)二次回归正交旋转设计,SAS程序及输出结果如下:
[size=150:24qc6z4y]程序:[/size:24qc6z4y]data new2;
input y x1 x2 x3 x4 @@;
x11=x1*x1-0.594;
x22=x2*x2-0.594;
x33=x3*x3-0.594;
x44=x4*x4-0.594;
cards;
11.52 1 1 1 1
16.88 1 1 -1 -1
8.77 1 -1 1 -1
9.18 1 -1 -1 1
12.58 -1 1 1 -1
10.68 -1 1 -1 1
9.98 -1 -1 1 1
10.61 -1 -1 -1 -1
12.34 -1.682 0 0 0
5.89 1.682 0 0 0
11.30 0 -1.682 0 0
14.84 0 1.682 0 0
11.38 0 0 -1.682 0
15.45 0 0 1.682 0
11.23 0 0 0 -1.682
10.97 0 0 0 1.682
12.94 0 0 0 0
13.44 0 0 0 0
12.91 0 0 0 0
17.19 0 0 0 0
11.55 0 0 0 0
13.29 0 0 0 0
13.68 0 0 0 0
;
proc glm;
model y=x1 x2 x3 x4 x1*x2 x1*x3 x1*x4 x2*x3 x2*x4 x3*x4 x11 x22 x33 x44;
title "二";
run;
proc corr;
var y x1 x2 x3 x4;
run;
[size=150:24qc6z4y]输出结果:[/size:24qc6z4y]
The GLM Procedure
Dependent Variable: y
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 11 96.6136460 8.7830587 1.97 0.1375
Error 11 48.9682410 4.4516583
Corrected Total 22 145.5818870
R-Square Coeff Var Root MSE y Mean
0.663638 17.41837 2.109895 12.11304
Source DF Type I SS Mean Square F Value Pr > F
x1 1 5.10344601 5.10344601 1.15 0.3072
x2 1 26.63798150 26.63798150 5.98 0.0325
x3 1 0.40286984 0.40286984 0.09 0.7692
x4 1 4.58945803 4.58945803 1.03 0.3317
x1*x2 1 7.56605000 7.56605000 1.70 0.2190
x1*x3 1 6.19520000 6.19520000 1.39 0.2630
x1*x4 1 0.73205000 0.73205000 0.16 0.6929
x2*x3 0 0.00000000 . . .
x2*x4 0 0.00000000 . . .
x3*x4 0 0.00000000 . . .
x11 1 35.23754280 35.23754280 7.92 0.0169
x22 1 0.13309807 0.13309807 0.03 0.8659
x33 1 0.01494004 0.01494004 0.00 0.9548
x44 1 10.00100972 10.00100972 2.25 0.1620
Source DF Type III SS Mean Square F Value Pr > F
x1 1 5.10344601 5.10344601 1.15 0.3072
x2 1 26.63798150 26.63798150 5.98 0.0325
x3 1 0.40286984 0.40286984 0.09 0.7692
x4 1 4.58945803 4.58945803 1.03 0.3317
x1*x2 0 0.00000000 . . .
x1*x3 0 0.00000000 . . .
x1*x4 0 0.00000000 . . .
x2*x3 0 0.00000000 . . .
x2*x4 0 0.00000000 . . .
x3*x4 0 0.00000000 . . .
x11 1 35.51820374 35.51820374 7.98 0.0165
x22 1 0.14922588 0.14922588 0.03 0.8581
x33 1 0.00997583 0.00997583 0.00 0.9631
x44 1 10.00100972 10.00100972 2.25 0.1620
The GLM Procedure
Dependent Variable: y
Standard
Parameter Estimate Error t Value Pr > |t|
Intercept 12.11265850 0.43994362 27.53 <.0001
x1 -0.61127167 0.57090443 -1.07 0.3072
x2 1.39653929 0.57090443 2.45 0.0325
x3 0.17174531 0.57090443 0.30 0.7692
x4 -0.57967318 0.57090443 -1.02 0.3317
x1*x2 0.97250000 B 0.74596064 1.30 0.2190
x1*x3 -0.88000000 B 0.74596064 -1.18 0.2630
x1*x4 -0.30250000 B 0.74596064 -0.41 0.6929
x2*x3 0.00000000 B . . .
x2*x4 0.00000000 B . . .
x3*x4 0.00000000 B . . .
x11 -1.49485281 0.52921707 -2.82 0.0165
x22 -0.09689358 0.52921707 -0.18 0.8581
x33 0.02505229 0.52921707 0.05 0.9631
x44 -0.79322220 0.52921707 -1.50 0.1620
[color=#0000FF:24qc6z4y]NOTE: The X'X matrix has been found to be singular, and a generalized inverse was used to solve the normal equations. Terms whose estimates are followed by the letter 'B' are not uniquely estimable.[/color:24qc6z4y]
[size=150:24qc6z4y] 版面看起来很不舒服,报歉! 不知道什么原因,有几个交互作用分析不出来,LOG窗口没显示错误信息,结果输出窗口有如上所示的蓝色字体提示,请高手指教!万分感谢![/size:24qc6z4y] |
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