[R] how to interpret coefficients for a natural spline smooth function in a GLM

[David Winsemius]

Plot the predictions; you can almost never interpret the coefficients  
of a spline fit individually. They are not really independent or  
separately interpretable.

Is this homework?
-- 
David
On Jun 15, 2009, at 10:19 AM, ltracy wrote:

>
> Hello-
>
> I am trying to model infections counts over 120 months using a GLM  
> in R.
> The model is simple really including a factor variable for year (10  
> yrs in
> total) and another variable consisting of a natural spline function  
> for time
> in months.
>
> My code for the GLM is as follows:
> model1<-glm(ALL_COUNT~factor(FY)+ns(1:120, 10), offset=log(TOTAL_PTS),
> family=poisson, data=TS1)
>
> The summary output pertaining to the smooth function consists of 10
> coefficients for each df in the model.  Here are the coefficients:
>
> ns(1:120, 10)1  -0.72438    0.32773  -2.210 0.027084 *
> ns(1:120, 10)2  -1.19097    0.37492  -3.177 0.001490 **
> ns(1:120, 10)3  -1.40250    0.42366  -3.310 0.000931 ***
> ns(1:120, 10)4  -0.82722    0.47459  -1.743 0.081334 .
> ns(1:120, 10)5  -0.46139    0.49657  -0.929 0.352812
> ns(1:120, 10)6  -0.44892    0.51909  -0.865 0.387137
> ns(1:120, 10)7  -0.53060    0.54783  -0.969 0.332778
> ns(1:120, 10)8  -0.25699    0.55582  -0.462 0.643814
> ns(1:120, 10)9  -0.74091    0.63899  -1.160 0.246249
> ns(1:120, 10)10  0.41142    0.56317   0.731 0.465054
>
> What is still unclear to me is what these 10 coefficients from the  
> natural
> spline represent.
>
> Thanks in advace-
>
>
>
>
> -- 
> View this message in context: http://www.nabble.com/how-to-interpret-coefficients-for-a-natural-spline-smooth-function-in-a-GLM-tp24035485p24035485.html
> Sent from the R help mailing list archive at Nabble.com.
>
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> and provide commented, minimal, self-contained, reproducible code.

David Winsemius, MD
Heritage Laboratories
West Hartford, CT