Hi everyone, I am running a multivariate linear regression with two categorical variables and five continuous variables included in the model. I understand there may be an issue with having too many parameters in the model with a small sample size (n~60) but I am working on removing some variables. That being said, I have two questions regarding the output below. 1) Statistically, why are all the reference groups equal to the intercept? I know they are not statistically significant in this model but if they were to be and if I were to interpret them, how do I explain that cat_variable1 and cat_variable2 reference groups have the same mean # for y? 2) Looking at the output for categorical variable 1, cat_variable1-1 is statistically significant (p-value=0.0243). When interpreting this we would say: on average, the difference between cat_variable 1-1 and the reference group is -30.7 units when controlling for... or even the average y for cat_variable1-1 is (23.25-30.7) when controlling for... However, clinically a negative average is not possible for cat_variable1-1. Can anyone explain this to me? Or am I interpreting this wrong? Thank you in advance! Code: proc glm data= final; class cat_variable1 (ref="0") cat_variable2 (ref="0"); model y =cat_variable1 x1 x2 x3 cat_variable2 x4 x5 / solution; run; Output: Parameter Estimate Standard Error t Value Pr > |t| Intercept 23.25202936 B 52.02075379 0.45 0.6568 categorical variable 1-1 -30.73950086 B 13.23227919 -2.32 0.0243 categorical variable 1-0 (reference group) 0.00000000 B . . . continuous variable 1 (x1) 0.22038763 0.66338254 0.33 0.7411 continuous variable 2 (x2) -0.04452906 0.91766027 -0.05 0.9615 continuous variable 3 (x3) 10.07999861 13.84172795 0.73 0.4699 categorical variable 2-1 7.29589112 B 17.81543974 0.41 0.6839 categorical variable 2-2 -11.89832386 B 27.73216991 -0.43 0.6697 categorical variable 2-3 -37.00121469 B 31.06097733 -1.19 0.2392 categorical variable 2-0 (reference group) 0.00000000 B . . . continuous variable 4 (x4) 0.18614679 0.06868578 2.71 0.0092 continuous variable 5 (x5) -2.83648236 4.03778253 -0.70 0.4856
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