similar to: lme and mixed effects

In my undertstanding of the problem, the model lme1 <- lme(resp~fact1*fact2, random=~1|subj) should be ok, providing that variances are homogenous both between & within subjects. The function will sort out which factors & interactions are to be compared within subjects, & which between subjects. The problem with df's arises (for lme() in nlme, but not in lme4), when

Dear ExpeRts, Suppose I have a typical psychological experiment that is a within-subjects design with multiple crossed variables and a continuous response variable. Subjects are considered a random effect. So I could model > aov1 <- aov(resp~fact1*fact2+Error(subj/(fact1*fact2)) However, this only holds for orthogonal designs with equal numbers of observation and no missing values.

Dear R-users, consider the two following outputs, ## 1 and ## 2 \begin{Scode}{Setup, echo = FALSE, print = FALSE, eval = TRUE} with(expand.grid(Fact1 = 1:3, Fact2 = 1:40), table(Fact1, Fact2)) ## 1 xtable(with(expand.grid(Fact1 = 1:3, Fact2 = 1:40), table(Fact1, Fact2))) ## 2 \end{Scode} The first line with(expand.grid(Fact1 = 1:3, Fact2 = 1:40), table(Fact1, Fact2))

I am trying to construct a two-way table where, instead of printing the two-way frequencies in the table, I would like to print the values of a third variable that correspond to the frequencies. For example, the following is easily constructed in R > fact1 <- factor(sample(LETTERS[1:3],10,replace=TRUE)) > fact2 <- factor(sample(LETTERS[25:26],10,replace=TRUE)) > fact3

I am using R to make two-way ANOVA on a number of variables using g <- aov(var ~ fact1*fact2) where var is a matrix containing the variables. However the outcome seem to be dependent on the order of fact1 and fact2 (i.e. fact2*fact1) gives a slightly (factor of 1.5) different result. Any ideas why this is? Thanks for any help Anders

The message for aov1 was "Estimated effects <may> be unbalanced". The effects are not unbalanced. The design is 'orthogonal'. The problem is that there are not enough degrees of freedom to estimate all those error terms. If you change the model to: aov1 <- aov(RT~fact1*fact2*fact3+Error(sub/(fact1+fact2+fact3)),data=myData) or to aov2 <-

Hello all, I have some trouble in reconstructing a valid expression within a function, here is my question. I am building a function : SUB<-function(DF,subset=TRUE) { #where DF is a data frame, with Var1, Var2, Fact1, Fact2, Fact3 #and subset would be an expression, eg. Fact3 == 1 #in a first time I want to build a subset from DF #I managed to, with an expression like eg. DF$Fact3, # but I

Hello, I am a new user or R, and am so far very impressed with its capabilities. However, I have no programming experience, and am having some issues in trying to tell the software what I want done. There are basically two issues which I am currently grappling with. The first, I have a data matrix, with two factors and dozens of response variables. I am interested on conducting ANOVAs on

I am trying to put 3 dotcharts side-by-side with minimal space between each. Each chart is for a different variable, but the vertical axes are the same. I want to have vertical axis labels on the lefthand chart but no vertical axis labels on the other two. Plus, I would like very little space between charts 1 & 2 and between charts 2 & 3. I have one approach but am not too happy with

Hi list, This is a very basic question about lattice: I wish to add some vertical lines in each panel of a xyplot as demonstrated in this example: > library(lattice) > > xx <- seq(1, 10, length=100) > x <- rep(xx, 4) > y <- c(cos(xx), sin(xx), xx, xx^2/10) > fact <- factor(rep(c("cos", "sin", "id", "square"), each=100))

Dear list, I've been trying this for a few hours and I just don't understand how lattice works with groups and subscripts. Consider the following example, > xx <- seq(1, 10, length=100) > x <- rep(xx, 4) > y <- c(cos(xx), sin(xx), xx, xx^2/10) > fact <- factor(rep(c("cos", "sin", "id", "square"), each=100)) > fact2

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

Dear R-helpers, I'm trying to selectively swap labels between two factors, depending on an indicator variable i. Can you point me to a solution, and perhaps how I could have found it? labels(fact1) is a character vector of r row numbers levels(fact1) is a character vector of the n < r unique levels How do I then get the character vector of length r of the levels of fact1? Once I have

Dear all, The following example code produces a graph with ggplot2, to which I add several vertical lines of arbitrary colors. I am not satisfied with the legend: it automatically adds some vertical lines which I'd rather not see (they confuse the reader rather than add information in this case). > library(ggplot2) > dfr <- data.frame(values = sin(1:50/10), > fact =

Hello to all users and wizards. I am regulary using 'boxplot' function or its analogue - 'bwplot' from the 'lattice' library. But they are, as far as I understand, totally flawed in functionality: they miss ability to select what they would draw 'in the middle' - median, mean. What the box means - standard error, 90% or something else. What the whiskers mean -

Hi List, Say I have a data.frame "DF" with 6 columns, 3 factors and 3 variables, with different number of repetitions for each combination of factors. I would like to build, for two given factors, a matrix per variable, containing in each cell the mean or sd for a given couple of factors. I have managed to get to the result I wanted step by step, but I would like to have it in a

--Apple-Mail-27-953181986 Content-Transfer-Encoding: 7bit Content-Type: text/plain; charset=US-ASCII; format=flowed a possible bug with survival analysis - either in R or in SPSS... find more details in bug.doc, and the data in bug.txt best Pius Korner --Apple-Mail-27-953181986 Content-Disposition: attachment Content-Type: multipart/appledouble; boundary=Apple-Mail-28-953181987

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

I am driving a Suse 8.2 linux with cups 1.1.18 and samba 2.2.7a. The problem: The host serves several printers via cups. If some jobs are in one of the queues "lpq -Pprinter" or "lpstat -o printer" shows up the complete listing. Fine. Connected to the same print queue from a Windows (XP/NT/98/2k) box I cannot see the complete listing. Sometimes I see some of the jobs, most of

Christoph Litauer <litauer@uni-koblenz.de> wrote on CUPS digest: > Message: 6 > From: Christoph Litauer <litauer@uni-koblenz.de> > Date: Wed, 14 May 2003 17:45:49 +0200 > Organization: Easy Software Products > To: cups@easysw.com > Subject: [cups.general] Re: [Samba] windows printer queue failure > Reply-To: cups@easysw.com > > Christoph Litauer wrote: >