Hi Statalist,

I just recently started working with restricted cubic splines using the mkspline/mkspline2 commands, and have some trouble interpreting the regression coefficients. I tried searching the forum but did not find a clear answer to my questions; any help is greatly appreciated!
  1. The documentation of mkspline says the coefficients measure, by default, the slopes for the interval. But from what I understand, the interval between two knots is not linear for a cubic spline, so is this a sort of “average” slope across the interval? Or the slope at the knot? Or something else?
  2. When using the spline in a logistic regression model, can I simply – as usual – exponentiate the coefficient to obtain an OR for the interval?
  3. To determine whether a variable is “significantly” associated with the outcome, is it sufficient if one single slope “significantly” differs from 0, or is there some way to test the “overall significance” of the variable taking into account the whole range of values? I could imaging that multiplicity could be an issue if I test multiple slopes for one variable and conclude a “significant” relationship if one single slope happens to be significant.
Thank you very much for any answers!

Best regards,
Patrick