From: Spencer Graves <spencer.graves_at_pdf.com>

Date: Sun 17 Jul 2005 - 11:22:04 EST

Date: Sun 17 Jul 2005 - 11:22:04 EST

Have you tried "anova(fit1, fit2)", where

fit1 <- lme(one model...) fit2 <- lme(a submodel ... )

This "anova" does about the best that anyone knows how to do -- or at lest did 7 years ago when it was written. If the "submodel" changes the fixed effects, you should use "method='ML'". If the "submodel" changes the noise model specification, use "method='REML'". See Pinheiro and Bates (2000) Mixed-Effect Models in S and S-Plus (Springer). If you need something more precise than the standard approximations, try "simulate.lme".

buena suerte! spencer graves

Patricia Balvanera wrote:

> Dear R users,

*>
**> I am using lme and nlme to account for spatially correlated errors as
**> random effects. My basic question is about being able to correct F, p, R2
**> and parameters of models that do not take into account the nature of such
**> errors using gls, glm or nlm and replace them for new F, p, R2 and
**> parameters using lme and nlme as random effects.
**>
**> I am studying distribution patterns of 50 tree species along a gradient.
**> That gradient
**> was sampled through 27 transects, with 10 plots within each transect. For
**> each plot I
**> have data on presence/absence, abundance and basal area of the species. I
**> also have data
**> for 4 environmental variables related to water availability (soil water
**> retention
**> capacity, slope, insolation, altitude) and X and Y coordinates for each
**> plot. I explored
**> wether the relationship between any of the response variables
**> (presence/absence,
**> abundance, basal area) and the environmental variables was linear,
**> polinomial, or
**> non-linear.
**>
**> My main interest in this question is that I proceeded to correct for spatial
**> autocorrelation (both within transects and overall) following the
**> procedures suggest by
**> Crawley 2002 for linear models
**> e.g. (GUAMAC = a species, CRAS = soil water retention capacity, TRANSECTO =
**> transect)
**> > model1<-gls(GUAMAC ~ CRAS)
**> > model2<-lme(GUAMAC ~ CRAS, random = ~ 1 | TRANSECTO)
**> > model3<-lme(GUAMAC ~ CRAS, random = GUAMAC ~ CRAS | TRANSECTO)
**> > model4<-lme(GUAMAC ~ CRAS, random = GUAMAC ~ CRAS -1 | TRANSECTO)
**> > AIC(model1,model2,model3,model4)
**> df AIC
**> model1 3 3730.537
**> model2 4 3698.849
**> model3 6 3702.408
**> model4 4 3704.722
**> > plot(Variogram(model2, form = ~ X + Y))
**> > model5<-update(model2,corr=corSpher(c(30,0.8), form = ~ X + Y, nugget = T))
**> > plot(Variogram(modelo7, resType = "n"))
**> > summary(model5)
**>
**> In this case I obtain new F for the independent variable INSOLACION, new R2
**> for the whole model and new parameters for the linear model.
**>
**> I have also applied this procedure to polinomial models and to glms with
**> binomial errors
**> (presence/absence) with no problem.
**>
**> I am nevertheless stuck with non-linear models. I am using the protocols
**> you suggested
**> in the 1998 manuals by Pinheiro and Bates, and those suggested by Crawley
**> 2002.
**> Please find enclose an example with an
**> exponential model (which I chose for being simple). In fact the linear
**> models I am using
**> are a bit more complicated.
**> (HELLOT is a species, INSOLACION = INSOLATION, basal = basal area of the
**> species, TRANSECTO = transect)
**>
**> > HELLOT ~ exp(A + (B * INSOLACION))
**> > basal.HELLOT <-function(A,B,INSOLACION) exp(A + (B * INSOLACION))
**> > HELLOT ~ basal.HELLOT(A,B,INSOLACION)
**> > basal.HELLOT<- deriv(~ exp(A + (B * INSOLACION))
**> + , LETTERS [1:2], function(A, B, INSOLACION){})
**> > model1<- nlme(model = HELLOT ~ exp(A + (B * INSOLACION)), fixed = A + B
**> ~ 1,
**> random = A + B ~ 1, groups = ~ TRANSECTO, start = list(fixed = c(5.23, -0.05)))
**>
**> It runs perfectly and gives new values for parameters A and B, but would
**> only give me F for fixed effects of A and B, while what I am really looking
**> for is F for fixed effects of INSOLACION and the R2 of the new model.
**>
**> Thank you so much in advance for your help
**>
**>
**>
**> Dra. Patricia Balvanera
**> Centro de Investigaciones en Ecosistemas, UNAM-Campus Morelia
**> Apdo. Postal 27-3, Xangari
**> 58090 Morelia, Michoacán, Mexico
**> Tel. (52-443)3-22-27-07, (52-55) 56-23-27-07
**> FAX (52-443) 3-22-27-19, (52-55) 56-23-27-19
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
*

-- Spencer Graves, PhD Senior Development Engineer PDF Solutions, Inc. 333 West San Carlos Street Suite 700 San Jose, CA 95110, USA spencer.graves@pdf.com www.pdf.com <http://www.pdf.com> Tel: 408-938-4420 Fax: 408-280-7915 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Sun Jul 17 11:24:49 2005

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