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Linear contrasts on data file friendly on page 209. The option /E on the contrast statement gives the entire vector.
proc means data=friendly;
class cond;
var correct;
run;
proc glm data=friendly;
class cond;
model correct=cond;
contrast 'SRF vs. others' cond -0.5 -0.5 1 /E;
contrast 'B vs. M' cond 1 -1 0 /E;
run;
quit;
The MEANS Procedure
Analysis Variable : correct
N
cond Obs N Mean Std Dev Minimum Maximum
-------------------------------------------------------------------------------------
Before 10 10 36.6000000 5.3374984 24.0000000 40.0000000
Meshed 10 10 36.6000000 3.0258149 30.0000000 40.0000000
SFR 10 10 30.3000000 7.3340909 21.0000000 39.0000000
-------------------------------------------------------------------------------------
The GLM Procedure
Class Level Information
Class Levels Values
cond 3 Before Meshed SFR
Number of observations 30
The GLM Procedure
Coefficients for Contrast SRF vs. others
Row 1
Intercept 0
cond Before -0.5
cond Meshed -0.5
cond SFR 1
The GLM Procedure
Coefficients for Contrast B vs. M
Row 1
Intercept 0
cond Before 1
cond Meshed -1
cond SFR 0
The GLM Procedure
Dependent Variable: correct
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 2 264.600000 132.300000 4.34 0.0232
Error 27 822.900000 30.477778
Corrected Total 29 1087.500000
R-Square Coeff Var Root MSE correct Mean
0.243310 16.00194 5.520668 34.50000
Source DF Type I SS Mean Square F Value Pr > F
cond 2 264.6000000 132.3000000 4.34 0.0232
Source DF Type III SS Mean Square F Value Pr > F
cond 2 264.6000000 132.3000000 4.34 0.0232
Contrast DF Contrast SS Mean Square F Value Pr > F
SRF vs. others 1 264.6000000 264.6000000 8.68 0.0065
B vs. M 1 0.0000000 0.0000000 0.00 1.0000
Calculation on page 214 and calculation on page 222 using data file duncan.
data inpt;
set duncan;
incpt=1;
run;
proc iml;
use inpt;
read all;
x = incpt || income || educ ;
b=INV(x`*x)*x`*prestige;
print b; /*regression coefficients*/
r=prestige-x*b;
v=(r`*r)/42;
V2=v*INV(x`*x);
d=diag(V2);
a=sqrt(d);
print a; /*estimated standard errors */
quit;
B
-6.064663
0.5987328
0.5458339
A
4.2719412 0 0
0 0.1196673 0
0 0 0.0982526
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