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. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
