> Date: Sat, 6 Nov 2010 07:45:26 -0700 > From: gunter.ber...@gene.com > To: sibylle.stoec...@gmx.ch > CC: r-help@r-project.org > Subject: Re: [R] anova(lme.model) > > Sounds to me like you should really be seeking help from your local > statistician, not this list. What you request probably cannot be done.
I'm still bringing my install up to speed so I can't immediately read the cited R stuff below but it sounds like the OP mentions a controversy documented in the R packages. Is there a list for discussing these topics? Offhand that seems legitimate for a user help list unless you want people to believe that " it came out of a computer so it must be right, whatever a P value is." > > What is wrong with what you get from lme, whose results seem fairly > clear whether the P values are accurate or not? > > Cheers, > Bert > > > > > > On Sat, Nov 6, 2010 at 4:04 AM, "Sibylle Stöckli" > wrote: > > Dear R users > > > > Topic: Linear effect model fitting using the nlme package (recomended by > > Pinheiro et al. 2008 for unbalanced data set). > > > > The R help provides much info about the controversy to use the > > anova(lme.model) function to present numerator df and F values. > > Additionally different p-values calculated by lme and anova are reported. > > However, I come across the same problem, and I would very much appreciate > > some R help to fit an anova function to get similar p-values compared to > > the lme function and additionally to provide corresponding F-values. I > > tried to use contrasts and to deal with the ‚unbalanced data set’. > > > > Thanks > > Sibylle > > > >> Kaltenborn<-read.table("Kaltenborn_YEARS.txt", na.strings="*", header=TRUE) > >> > >> > >> library(nlme) > > > >> model5c<-lme(asin(sqrt(PropMortality))~Diversity+ > >> Management+Species+Height+Height*Diversity, data=Kaltenborn, > >> random=~1|Plot/SubPlot, na.action=na.omit, > >> weights=varPower(form=~Diversity), subset=Kaltenborn$ADDspecies!=1, > >> method="ML") > > > >> summary(model5c) > > Linear mixed-effects model fit by maximum likelihood > > Data: Kaltenborn > > Subset: Kaltenborn$ADDspecies != 1 > > AIC BIC logLik > > -249.3509 -205.4723 137.6755 > > > > Random effects: > > Formula: ~1 | Plot > > (Intercept) > > StdDev: 0.06162279 > > > > Formula: ~1 | SubPlot %in% Plot > > (Intercept) Residual > > StdDev: 0.03942785 0.05946185 > > > > Variance function: > > Structure: Power of variance covariate > > Formula: ~Diversity > > Parameter estimates: > > power > > 0.7302087 > > Fixed effects: asin(sqrt(PropMortality)) ~ Diversity + Management + Species > > + Height + Height * Diversity > > Value Std.Error DF t-value p-value > > (Intercept) 0.5422893 0.05923691 163 9.154585 0.0000 > > Diversity -0.0734688 0.02333159 14 -3.148896 0.0071 > > Managementm+ 0.0217734 0.02283375 30 0.953562 0.3479 > > Managementu -0.0557160 0.02286694 30 -2.436532 0.0210 > > SpeciesPab -0.2058763 0.02763737 163 -7.449198 0.0000 > > SpeciesPm 0.0308005 0.02827782 163 1.089210 0.2777 > > SpeciesQp 0.0968051 0.02689327 163 3.599602 0.0004 > > Height -0.0017579 0.00031667 163 -5.551251 0.0000 > > Diversity:Height 0.0005122 0.00014443 163 3.546270 0.0005 > > Correlation: > > (Intr) Dvrsty Mngmn+ Mngmnt SpcsPb SpcsPm SpcsQp Height > > Diversity -0.867 > > Managementm+ -0.173 -0.019 > > Managementu -0.206 0.005 0.499 > > SpeciesPab -0.253 0.085 0.000 0.035 > > SpeciesPm -0.239 0.058 0.001 0.064 0.521 > > SpeciesQp -0.250 0.041 -0.001 0.032 0.502 0.506 > > Height -0.518 0.532 -0.037 -0.004 0.038 0.004 0.033 > > Diversity:Height 0.492 -0.581 0.031 -0.008 -0.149 -0.099 -0.069 -0.904 > > > > Standardized Within-Group Residuals: > > Min Q1 Med Q3 Max > > -2.99290873 -0.60522612 -0.05756772 0.62163049 2.80811502 > > > > Number of Observations: 216 > > Number of Groups: > > Plot SubPlot %in% Plot > > 16 48 > > > >> anova(model5c) > > numDF denDF F-value p-value > > (Intercept) 1 163 244.67887 <.0001 > > Diversity 1 14 1.53025 0.2364 > > Management 2 30 6.01972 0.0063 > > Species 3 163 51.86699 <.0001 > > Height 1 163 30.08090 <.0001 > > Diversity:Height 1 163 12.57603 0.0005 > >> > > > > -- > Bert Gunter > Genentech Nonclinical Biostatistics > Mike Marchywka | V.P. Technology 415-264-8477 marchy...@phluant.com Online Advertising and Analytics for Mobile http://www.phluant.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.