similar to: testing for significance in random-effect factors using lmer

Hi, I have tried to run the following (I know it's a huge data set but I tried to perform it with a 1 GB RAM computer): library(foreign) library(MASS) library(nlme) datos<-read.spss(file="c:\\Documents and Settings\\Administrador\\Escritorio\\datosfin.sav",to.data.frame=TRUE) str(datos) `data.frame': 1414 obs. of 5 variables: $ POB : Factor w/ 6 levels

Dear helpers, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

LS, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

Dear All, I'm trying to model heteroscedasticity using a multilevel model. To do so, I make use of the nlme package and the weigths-parameter. Let's say that I hypothesize that the exam score of students (normexam) is influenced by their score on a standardized LR test (standLRT). Students are of course nested in "schools". These variables are contained in the

LS, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

Hi, trying to do a robudt regression of a two-way linear model, I keep getting the following error: > lqs(obs ~ y + s -1,method="lms", contrasts=list(s=("contr.sum"))) Error: lqs failed: all the samples were singular Robust regression with M-estimators works (also regular least square fits, of course): rlm.formula(formula = obs ~ y + s - 1, method = "M",

Hello I will appreciate your help with the following. Running a script in R 2.14.1 under windows vista I get the following error message: Error in ifelse(append, "a", "w") : (list) object cannot be coerced to type 'logical' However, the very same script runs perfectly well under Ubuntu. My understanding is that this type of error is associated to

Hello This is a simple question but I couldn't google an answer. In the procrustes function of the vegan package, one uses plot(procrustes_object, kind=2) to obtain a plot of the residual differences. For instance: data(varespec) vare.dist <- vegdist(wisconsin(varespec)) library(MASS) mds.null <- isoMDS(vare.dist, tol=1e-7) mds.alt <- isoMDS(vare.dist,

Hi, I'm trying to install de RSPerl module and i have some problems trying to test it. I've tried to contact with the author but the e-mail address seems not to exist. Hope that anyone in this list could explain me a little about this problem. I have a bash shell and what i do is the following: #PERLLIB=/usr/lib/R/library/RSPerl/share/blib/arch:/usr/lib/R/library/RSPerl/share/blib/lib #

Hi, I am doing my way on R, with much experimenting. So, I am trying to plot a 3d graphic ussing "persp" and entering a data set (attached) of UTM coordinates as x,y and a pH values as z. However when I try an error message comes out telling that increasing x and y values are expected. Jus ordering the first vector does not help, and, of course, order the first two independently

Hello I would appreciate your help on the followig. I want to generate random binary matrices but I need to discard those with all-1 rows. That is, for a 10x10 matrix with five 1's [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0 0 0 0 0 0 0 0 0 1 [2,] 0 0 0 0 0 0 1 0 0 0 [3,] 0 0 0 0 0 0 1

Hi List, I have to compare a relationship between y and x for two locations. I found logistic regression fits both datasets well, but I am not sure how to test if relationships for both sites are significantly different. I searched the r site, however no answers exactly match the question. I used Tukey's HSD to compare two means, but the relationship in my study was not simply linear. So I

Hello, I wanted to fit a linear mixed model to a data that is similar in terms of design to the 'Machines' data in 'nlme' package except that each worker (with triplicates) only operates one machine. I created a subset of observations from 'Machines' data such that it looks the same as the data I wanted to fit the model with (see code below). I fitted a model in

Hi, after a debian upgrade my dev.copy2eps dont work anymore. I have this message: Error in matchFont(postscriptFonts(family)[[1]], old$encoding) : unknown font I try to change the font family in my .Rprofile: setHook(packageEvent("graphics", "onLoad"), function(...) { grDevices::ps.options(family="ComputerModern") } ) But it no fix

My question concerns the logic behind hypothesis tests for fixed-effect terms in models fitted with lme. Suppose the levels of Subj indicate a grouping structure (k subjects) and Trt is a two-level factor (two treatments) for which there are several (n) responses y from each treatment and subject combination. If one suspects a subject by treatment interaction, either of the following models seem

Hi all, I am having issues comparing models with lmer. As an example, when I run the code below the model summaries (AIC, BIC, loglik) differ between the summary() and anova() commands. Can anyone clear up what's wrong? Thank you! Darren Ward library(lme4) data(sleepstudy) fm1<-lmer(Reaction ~ Days + (1|Subject), sleepstudy) summary(fm1) fm2<-lmer(Reaction ~ Days +

Dear R user: I bulid a package, and in the package I use the function "nls" to solve some questions. If I have two sets of data, and I want to summary these two data's nls output, I write the command in the package source code like: { .......... summary(fm1) summary(fm2) } then i compiler the package and use "Install package(s) from local zip files" to install my

Hi, I have a string that I want to use in a variable call. How can I remove the quotes and/or the string properties of the string to use it in a variable call? Here's an example: library(lme) fm2 <- lme(distance ~ age, data = Orthodont, random = ~ 1) summary(fm2) I want to update the above regression to include new predictors according to what is in a string: predictors <-

Dear R-helpers, When I try > anova(txtE2.lme, txtE2.lme1) Model df AIC BIC logLik Test L.Ratio p-value txtE2.lme 1 10 8590 8638 -4285 txtE2.lme1 2 7 8591 8624 -4288 1 vs 2 6.79 0.0789 > latex(anova(txtE2.lme, txtE2.lme1)) Error: object "n.group" not found I don't even see n.group as one of the arguments of latex() I checked to see >

The subject says it all really. Question 1. Here is some code created to illustrate my problem, can anyone spot where I'm going wrong? Question 2. The reason I'm following a manual specification of models relates to the fact that in reality I am using mgcv::gam, and I'm not aware that dredge is able to separate individual smooth terms out of say s(a,b). Hence an additional request,