[R] Predicting complicated GAMMs on response scale
wdp1 at st-andrews.ac.uk
Mon May 18 20:48:44 CEST 2009
I am using GAMMs to show a relationship of temperature differential over
time with a model that looks like this:-
where DaysPT is time in days since injury and Diff is repeat measures of
temperature differentials with regards to injury sites compared to
non-injured sites in individuals over the course of 0-24 days. I use the
following code to plot this model on the response scale with 95% CIs which
However, when I add a correlation structure and/or a variance structure so
that the model may look like:-
I get this message at the point of inputting the line
Error in model.frame(formula, rownames, variables, varnames, extras,
variable lengths differ (found for 'DaysPT')
In addition: Warning messages:
1: not all required variables have been supplied in newdata!
in: predict.gam(g.m$gam, p.d, se = TRUE)
2: 'newdata' had 25 rows but variable(s) found have 248 rows
Is it possible to predict a more complicated model like this on the response
scale? How can I incorporate a correlation structure and variance structure
in a dataframe when using the predict function for GAMMs?
Any help would be greatly appreciated.
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