I have several variables that I think have non-linear effects. One way to address that is to generate splines. But as far as I can tell these do not generate anything like a slope. How do you interpret splines in terms of its impact on the DV?

Since I am brand new to this code I wanted to see if I did it correctly. All the class variables are dummies that can not be non-linear.

Following advice I saw I compared the AIC I got with this [non-linear I think or general additive] model to the one I got with proc genmod which does not assume non-linearity the way I ran it. The non-linear proc genmod model had a lower AIC (359317 versus 360676)

Does this mean I should not worry about the non-linear effect in interpreting the interval predictors I suspect are non-linear?

Since I am brand new to this code I wanted to see if I did it correctly. All the class variables are dummies that can not be non-linear.

Code:

```
proc gampl data=dora.fin plots seed=12345;
CLASS edclo ethd femaled SSDIALLOWED SD
SSIALLOWED WhiteD ;
model q2wage = spline(inserv) spline(sum_of_tuition) spline(rate)
;
output out=outs;
run;
```

Does this mean I should not worry about the non-linear effect in interpreting the interval predictors I suspect are non-linear?

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