The second model is:-
Log(crh)= b0 + b1*time + b2*hvinf + b3*(time*hvinf).
I can get similar prediction equations as above. In both these models, the intercept and the coefficient for time are same ie, b0 and b1 is same in both the regression models.
In both the above regression models, I included a quadratic term for time, modifying the models as given below:
Model-1: Log(crh)= b0 + b1*time + b2*time^2 + b3*hvptb + b4*(time*hvptb).
Model-2: Log(crh)= b0 + b1*time + b2*time^2 + b3*hvinf + b4*(time*hvinf).
On estimating the models I find that the values of b0 and b1 are not the same for the two models. Hence the prediction equation for the normal people are different in the two models. The quadratic time term is significant in the model.
Austin Nichols wrote back to me that the coefficients will be the same only if I include all the relevant interaction terms "time^2*hvptb" and "time^2*hvinf" also in the model. I verified this but I couldn't find a mathematical explanation to why this is so.
On including the interaction terms for time^2, I lose significance on those terms as well as the other terms. So if I leave out the interaction terms I need to explain why the normal people have different equations in the two models.
I'd appreciate any help on this issue.
Thanks,
Leny
Leny Mathew
Data Analyst
Division of Perinatal Research
Department of Obstetrics/Gynecology
Drexel University College of Medicine
245 N. 15th Street, 17th Floor
Mail Stop 495
Philadelphia, PA 19102
Phone: 215-762-2069
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