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ssanova help
2 messages · Josef Fruehwald, David Winsemius
On Aug 31, 2009, at 7:19 PM, Josef Fruehwald wrote:
Hi all, I'm using the ssanova function from the gss package to fit smoothing spline anovas, and am running into some difficulty. For my data, I have measurements at 2 milisecond intervals for every observation. Every observation does not have the same duration, so I have scaled the times for each observation to a scale between 0 and 1. I would like to smooth over time, and the following works: ssanova(Measurement ~ ScaleTime, data = data) I would also like to see how the variable duration affects the curve, so I have another column in the dataframe which contains the log duration. I did it like so: Durations <- data.frame(LogDuration = log(tapply(data$Time, data $Token, max)), Token = levels(data$Token)
That looks wrong. The results of tapply will not in general be a single number, so LogDuration could be a rather weird list of things. Have you run summary() on it?
data <- merge(data, Durations, by = "Token")
But maybe I am not really understanding your genius.
Now every measurement point for every observation also has the log(duration) of the entire observation associated with it. I would assume that the following is how I should specify my formula: ssanova(Measurement ~ ScaleTime * LogDuration, data = data)
I wonder if log time (once you confirm that the variable is what you want it to be) ought to be entered as an offset?
but I get the following error:
Error in if (!((2 * order > dm) & (dm >= 1))) { :
missing value where TRUE/FALSE needed
I get the same error if I try
ssanova(Measurement ~ LogDuration, data = data)
Any suggestions as to how I should approach this problem? I know
that if I
break duration into some kind of factor, I can successfully fit the
model.
However, I would like to assume that there is a continuous
transformation of
the curve shape as duration increases or decreases.
Thanks!
Joe
David Winsemius, MD Heritage Laboratories West Hartford, CT