Thanks. Here is a similar example from a book by Pinheiro and Bates (2000,
chapter 6):
library(nlme) data(Soybean)
fm1Soy.lis <- nlsList( weight ~ SSlogis(Time, Asym, xmid, scal), data =
Soybean ) fm1Soy.nlme <- nlme( fm1Soy.lis )
If we would like to make comparisons among the years we could just simply
involve years as a covariate, and later we could use L argument to ANOVA to
could compute contrasts.
soyFix <- fixef( fm1Soy.nlme ) fm2Soy.nlme <- update( fm1Soy.nlme, fixed =
Asym + xmid + scal ~ Year, start = c(soyFix[1], 0, 0, soyFix[2], 0, 0,
soyFix[3], 0, 0) )
My question is: How can I compare variety of soybeans in a separate month, i.e.
if there was a difference in weight of soybeans F and P in first month,
in
twelve month?
The dataset Soybean:
Plot Variety Year Time weight
1 1988F1 F 1988 14 0.106000
2 1988F1 F 1988 21 0.261000
3 1988F1 F 1988 28 0.666000
4 1988F1 F 1988 35 2.110000
5 1988F1 F 1988 42 3.560000
.
407 1990P8 P 1990 30 1.478330
408 1990P8 P 1990 37 2.601667
409 1990P8 P 1990 43 6.343330
410 1990P8 P 1990 51 6.131670
411 1990P8 P 1990 64 16.411700
412 1990P8 P 1990 79 16.946700
1) Involving months and variety as a covariates will probably create too
many parameters for the model?
2) Is it possible to use some test for comparisons, lets say t test?
Perhaps not in case the data are dependent (i.e. previous measurement is
dependent on the next measurement, i.e. there is temporal correlation (as in my
study of Soil temperature)? What is an alternative suggestion?
Thanks,
Julia> Date: Fri, 4 Jul 2008 17:36:29 -0700> From: [EMAIL PROTECTED]> To:
[EMAIL PROTECTED]> CC: r-help@r-project.org> Subject: Re: [R] Test for multiple
comparisons: Nonlinear model, autocorrelation?> > The question seems too
general for me to offer specific suggestions.> > What problem are you trying to
solve that you think 'multiple > comparisons' will answer?> > Can you produce a
similar problem that is completely self-contained > example that eliminates
complexity that may not be needed to understand > your question (similar to the
'Auxiliary Problem' technique in "How to > Solve It",
http://en.wikipedia.org/wiki/How_to_Solve_It)? If you can, it > may lead you to
a solution. If you get such an example but still can't > see a solution, send
that example to this list (following the advice in > the posting guide
http://www.R-project.org/posting-guide.html). The > simpler the example, the
more likely someone on this list will reply > quickly with a useful
suggestion.> > I know this doesn't solve your problem, but I hope it helps.>
Spencer> > J S wrote:> > Dear R community, > > > > I have a nonlinear model
describing average daily soil temperature. What test should I use to compare
differences in soil temperature of the two studied vegetation types depending
upon month?> > > > Building linear contrasts for the developed nonlinear model
does not help since this model does not include variable Months (only
Days). > > > > 1) Just a Students test is not probably an option because I
would violate an assumption of independency, since the daily soil temperature
observations have high autocorrelation. Or maybe I could average the
observations for each month and then use this test since I have observations
for a few years, and it might overcome the problem of independency?> > > > 2)
Should I develop a second nonlinear model with months instead of days, but it
would considerably increase a number of parameters in the model...> > > > Or:>
> 3) ?> > > > Thanks for your help,> > Julia> >
_________________________________________________________________> > Its a
talkathon but its not just talk.> >> > [[alternative HTML version deleted]]>
>> > > >
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______________________________________________> > R-help@r-project.org mailing
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