1# sjliu0509
Question is not clear. I generated a dataset and run a proc reg. The code and results are as following. some explanation are in the code. Hope this will help you. Let me know what you think.
data test;
seed=123456;
do i=1 to 100;
weight=30*NORMAL(seed)+120;
height=1.3*weight+NORMAL(SEED);
output;
end;
run;
proc print data=test;
/*The White test tests the null hypothesis that the variance of the residuals is homogenous.
Therefore, if the p-value is very small, we would have to reject the hypothesis and
accept the alternative hypothesis that the variance is not homogenous.
We use the / spec option on the model statement to obtain the White test. */
proc reg;
model height=weight/ spec;
run;
The SAS System 16:14 Friday, May 15, 2009 53
The REG Procedure
Model: MODEL1
Dependent Variable: height
Number of Observations Read 100
Number of Observations Used 100
Analysis of Variance
Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 176720 176720 185416 <.0001
Error 98 93.40413 0.95310
Corrected Total 99 176814
Root MSE 0.97627 R-Square 0.9995
Dependent Mean 156.60601 Adj R-Sq 0.9995
Coeff Var 0.62339
Parameter Estimates
Parameter Standard
Variable DF Estimate Error t Value Pr > |t|
Intercept 1 0.21567 0.37608 0.57 0.5676
weight 1 1.29890 0.00302 430.60 <.0001
The SAS System 16:14 Friday, May 15, 2009 54
The REG Procedure
Model: MODEL1
Dependent Variable: height
Test of First and Second
Moment Specification
DF Chi-Square Pr > ChiSq
2 2.28 0.3206
it is not significant as which is what we expected.