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st: Explaining interaction terms
I have 2 questions regarding multiplicative regression models. I hope that the statisticians in the group can help me out.
1) I have a regression model with the dependent variable log-transformed and the first independent variable X1 as taking 0 if belonging to group1 and 1 if belonging to group2, and the second variable X2 denoting time. In this model both the independent variables are significant and it was seen that for the two cases of X1, the curves have different slopes.
I considered another model with an interaction term between X1 and X2. In the output, the group effect is not significant, but the interaction effect is.
Regression with robust standard errors Number of obs= 125
F( 3, 42) = 86.36
Prob > F = 0.0000
R-squared = 0.7339
Number of clusters (ID) = 43 Root MSE = .50028
lnY Coef. Std. Err. t P>t [95% Conf. Inter]
X2 .0826 .0098 8.43 0.0 .062 .102
X1 -.2171 .1892 -1.15 0.26 -.599 .164
X1X2 .0264 .0125 2.10 0.04 .001 .051
cons 1.91 .1536 12.42 0.0 1.598 2.218
In the above output how should one interpret the effect of the interaction term in the model? For group1, can we say that for a one unit change in X2, the value of y changes by a percentage? Or is the only way to express the increase in Y by specific value of X2?
2) In the same model as above is there a way to find the point where the slope starts to increase: (inflection point?) (I tried spline regression, but can’t get a good fitting model).
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org:Drexel University College of Medicine;OB/GYN control