similar to: plot.augPred sorted and labelled according second factor

Dear all as I did not get any response on my post about abline and plot(augPred)) I try again. I hope I do not break some posting guide rules. I would try to contact package maintainer directly but there is stated to be R-core people, so I feel R-help list shall be OK. I need to draw straight lines through augPred plotted panels (vertical or horizontal) at specified point. I know I shall

Hi, I'm new at this, I'm very confused, and I think I'm missing something important here. In our pet example we have this: > fm <- lme(Orthodont) > plot(Orthodont) > plot(augPred(fm, level = 0:1)) which gives us a trellis plot with the females above the males, starting with "F03", "F04", "F11", "F06", etc. I thought the point of

Hello, Is there a way to get augPred to work with lme if a subset statement is used? For example, if I modify the example from ?augPred.lme to include a subset statement, I get the following error: fm1 <- lme(Orthodont, random = ~1, subset=distance>19) augPred(fm1, length.out = 2, level = c(0,1)) Error in tapply(object[[nm]], groups, FUN[["numeric"]], ...) : arguments

Dea-R community. I'd like to draw your attention to an issue I have recently encountered while doing my current data analysis. I've got an unexpected (to me) result from the command: > augPred(lmList(my.object)), 'my.object' being a grouped data frame of class: > class(my.object) [1] "nfnGroupedData" "nfGroupedData" "groupedData"

All, I'm trying to create an augPred plot in the nlme library, similar to the plot on p.43 of Pinheiro & Bates (Mixed Effects Models in S and S-Plus) for their Pixel data. My data structure is the same as the example but I still get the error msg below. > comp.adj.UKV <- groupedData(adj.UKV ~ Time | Patient_no/Lisinopril, data = comp.adj.UKV.frm, order.groups = F) >

Dear all I am trying nlme together with Pinheiro/Bates book. I constructed grouped data object with suitable plotting layout (according to some common factor, panels from bottom to top are in increasing order). When I do nlme(... some stuff...) I get fitted object which I can plot with plot(augPred(fit.nlme6, level=0:1)) but it results in completely different ordering. Is there any way

Using formulas constructed from strings only partially works for me in lme: library(nlme) data(Orthodont) fm2<-lme(as.formula("distance~age"),data=Orthodont,random=~1|Subject) summary(fm2) # works augPred(fm2) # fails #Error in inherits(object, "formula") : #Argument "object" is missing, with no default I assume that my use of as.formula is wrong, but

Dear r-helpers, When I issue the commands plot(augPred(mcc.lme, primary = ~ mcc$age, length.out = 2, level = c (0, 1))) or plot(comparePred(mcc1.lis, mcc.lme, primary = ~ mcc$age, length.out = 2), layout = c(4, 3))) no lines are drawn. But fm1 <- lme(Orthodont) plot(augPred(fm1, level = 0:1, length.out = 2)) does plot lines. augPred() and comparePredict() seem to be working correctly, as

I want to compute confidence intervals for the random effect estimates for each subject. From checking on postings, this is what I cobbled together using Orthodont data.frame as an example. There was some discussion of how to properly access lmer slots and bVar, but I'm not sure I understood. Is the approach shown below correct? Rick B. # Orthodont is from nlme (can't have both nlme and

Hi Folks, I'm trying to understand the model specification formalities for 'lme', and the documentation is leaving me a bit confused. Specifically, using the example dataset 'Orthodont' in the 'nlme' package, first I use the invocation given in the example shown by "?lme": > fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age Despite the

dear all, I would like to get the lme call without fitting the relevant model. library(nlme) data(Orthodont) fm1 <- lme(distance ~ age, random=list(Subject=~age),data = Orthodont) To get fm1$call without fitting the model I use call(): my.cc<-call("lme.formula", fixed= distance ~ age, random = list(Subject = ~age)) However the two calls are not the same (apart from the data

Hi all, To follow up on an older thread, it was suggested that the following would produce confidence intervals for the estimated BLUPs from a linear mixed effect model: OrthoFem<-Orthodont[Orthodont$Sex=="Female",] fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem) fm1.s <- coef(fm1OrthF.)$Subject fm1.s.var <- fm1OrthF. at bVar$Subject fm1.s0.s <-

Hi, I'm having some problems regarding the packages lme4 and nlme, more specifically in the denominator degrees of freedom. I used data Orthodont for the two packages. The commands used are below. require(nlme) data(Orthodont) fm1<-lme(distance~age+ Sex, data=Orthodont,random=~1|Subject, method="REML") anova(fm1) numDF DenDF F-value p-value (Intercept) 1

Hello, How do I get the standard deviations for the random effects out of the lme object? I feel like there's probably a simple way of doing this, but I can't see it. Using the first example from the documentation: > fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age > fm1 Linear mixed-effects model fit by REML Data: Orthodont Log-restricted-likelihood:

Dear all I try to refine my nlme models and with partial success. The model is refined and fitted (using Pinheiro/Bates book as a tutorial) but when I try to plot plot(augPred(fit4)) I obtain Error in predict.nlme(object, value[1:(nrow(value)/nL), , drop = FALSE], : Levels (0,3.5],(3.5,5],(5,7],(7,Inf] not allowed for vykon.fac > Is it due to the fact that I have unbalanced

Dear R developers, first of all let me join the chorus of congratulations for the release of R 1.0.0. Well, done! Unfortunately, I find it necessary to e-mail in a bug report regarding the `nlme' package. On my office machine I experience the following trouble: bossiaea:/opt/R$ R CMD check -c nlme Checking package `nlme' ... Massaging examples into `nlme-Ex.R' ... Running

Dear friends. I tried the session below with 10 MB in both vsize and nsize but didn't get the example work. Is this a problem in LME or in me or both or somewhere else or undefined ? R : Copyright 1999, The R Development Core Team Version 0.64.0 Patched (May 3, 1999) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type

Hi everyone, I have a quick and probably easy question about lme for this list. Say, for instance you want to model growth in pituitary distance as a function of age in the Orthodont dataset. fm1 = lme(distance ~ I(age-8), random = ~ 1 + I(age-8) | Subject, data = Orthodont) You notice that there is substantial variability in the intercepts (initial distance) for people at 8 years, and that

Hello! If I run this example: library(nlme) fm1 <- lme(distance ~ age+Sex, Orthodont, random = ~ age + Sex| Subject) If I run: summary(fm1) then I can see the fixed effects for age and sex (17.7 for intercept, 0.66 for age, and -1.66 for SexFemale) If I run: ranef(fm1) Then it looks like it's producing the random effects for each subgroup (in this example - each subject). For example,

Dear List, I am plotting lmList objects using plot(intervals()) in nlme package. I want to make changes to the y-axis labels. When I try to change cex of y-axis labels using the following: fm1 <- lmList(distance ~ age | Subject, Orthodont) plot(intervals(fm1), scales=list(y=list(cex = .7))) I receive: Error in bwplot(formula = group ~ intervals | what, data = structure(list( : formal