Hi,
does anyone know how to interprate the fixed effects in Solutions when the intercept is canceled, such as Drug A, D,G and Gender F as below?
22.16666667 | B | 2.58800653 | 8.57 | <.0001 |
39.06666667 | B | 2.58800653 | 15.10 | <.0001 |
59.96666667 | B | 2.58800653 | 23.17 | <.0001 |
4.26666667 | B | 2.58800653 | 1.65 | 0.1113 |
0.00000000 | B | . | . | . |
Please see my code below:
proc glm data=DrugTest;
class Drug gender;
model Y = Drug GENDER/ noint solution;
run;
Thank you so much!
Nancy
Do you know how to interpret the coefficients for the intercept case? It's the same idea for the no-intercept model, except the intercept term is assigned to the last level of DRUG.
For males, the mean response is 22, 38, and 60 for Drugs A, D, and G, respectively.
For females, the mean response is 4.3 units higher at each level of DRUG.
If you turn on ODS graphics and put
PLOTS=IntPlot;
on the PROC GLM statement, you can see plots of the regression.
The results are re-posted as below
Parameter | Estimate |
| Standard Error | t Value | Pr > |t| |
Drug A | 22.16666667 |
| 2.58800653 | 8.57 | <.0001 |
Drug D | 39.06666667 |
| 2.58800653 | 15.10 | <.0001 |
Drug G | 59.96666667 |
| 2.58800653 | 23.17 | <.0001 |
Gender F | 4.26666667 |
| 2.58800653 | 1.65 | 0.1113 |
Gender M | 0.00000000 |
| . | . | . |
Do you know how to interpret the coefficients for the intercept case? It's the same idea for the no-intercept model, except the intercept term is assigned to the last level of DRUG.
For males, the mean response is 22, 38, and 60 for Drugs A, D, and G, respectively.
For females, the mean response is 4.3 units higher at each level of DRUG.
If you turn on ODS graphics and put
PLOTS=IntPlot;
on the PROC GLM statement, you can see plots of the regression.
Thank you very much, it is helpful!
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