I would approach something like this using predict(fit41$gam,...) (see
?predict.gam) to produce the data needed for the plots.
Another possibility is to use s(Time,trt,bs="fs") (but see
?factor.smooth.interaction first).
Note that gamm4 does not have a correlation argument, because lme4 does
not provide correlation structures, so corARH1() is just ignored (there
is no error or warning produced because gamm4 does have a '...' argument!).
best,
Simon
On 27/11/12 00:07, MurphFL wrote:
My problem is relatively straight forward, but I cannot seem to find a way to
make it work.
I have a RCBD with repeated measurements over time. I have created a fit
using the gamm4 package. My model is:
fit4a <- gamm4(Rate ~ s(Time,by=trt,bs="cr")+trt,data=qual.11.dat,
random=~(1|block),correlation=corARH1())
What I would like to create is plots with the X-axis being time, the Y-axis
being the fitted Rates for each individual treatment with the smoothed
curves overlayed on the plot.
Every idea I have had to do this has resulted in some errors, and I have
reached my wits end. Can anyone steer me in the right direction?
--
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--
Simon Wood, Mathematical Science, University of Bath BA2 7AY UK
+44 (0)1225 386603 http://people.bath.ac.uk/sw283
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