similar to: RE: [S] lme vs. aov with Error term

Hi, I have a question about using "lme" and "aov" for the following dataset. If I understand correctly, using "aov" with Error term in the formula is equivalent to using "lme" with default settings, i.e. both assume compound symmetry correlation structure. And I have found that equivalency in the past. However, with the follwing dataset, I got different

Hi, I have a question about using "lme" and "aov" for the following dataset. If I understand correctly, using "aov" with an Error term in the formula is equivalent to using "lme" with default settings, i.e. both assume compound symmetry correlation structure. And I have found that equivalency in the past. However, with the follwing dataset, I got different

Hi all, Sent the following question yesterday, but haven't got any suggestions yet. So just trying again, can anyone comment on the problem that I have? Thank you! ------------- Hi, I have a question about using "lme" and "aov" for the following dataset. If I understand correctly, using "aov" with an Error term in the formula is equivalent to using

Hello, I am running error rate analysis. It is my results below. When I compare aov1 and aov2, X square = 4.05, p = 0.044, which indicates that adding the factor "Congruity" improved the fitting of model. However, the following Z value is less than 1 and p value for Z is 1, which means that "Congruity" is not significant at all. Therefore, these two parts are not consistent,

Dear R-Community! The example "oats" in MASS (2nd edition, 10.3, p.309) is calculated for aov and lme without interaction term and the results are the same. But I have problems to reproduce the example aov with interaction in MASS (10.2, p.301) with lme. Here the script: library(MASS) library(nlme) options(contrasts = c("contr.treatment", "contr.poly")) # aov: Y ~

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 <-

G'day, I'm?calculating LSM for the following model, and am finding that R and SAS give different answers. Whilst the error is at the second or third decimal, the percentage error can be quite large. I'm using the effects library (Version: 2.0-10) on R?2.11.1 in the following manner: options(contrasts=c("contr.helmert","contr.poly"))

Not sure whether this is a feature or bug -- but it does not appear to be documented. R1.6.1 on Windows NT 4.00.1381 Objects assigned in the Rprofile.site file (e.g. foo<-'something') are put into package:base not .GlobalEnv on startup. Objects assigned in the .Rprofile file are put into .GlobalEnv. This doesn't seem consistent to me. The objects exist in base only for the

Folks: Winnt; R1.7.0 (freshly installed) running under Rgui.exe.,MDI=yes. The following is repeatable: On startup, in my Rprofile.site file, I use winMenuAdd() etc. to install some user menus. However, they do not appear when R GUI window opens. If I minimize and restore the window, the added menus now are present. The exact same procedure under 1.6.2 with exactly the same Rprofile.site and

All: The select.list() command brings up a "modal dialog box with a (scrollable) list of items ..." etc. -- i.e., a GUI control. I also know about winDialog, file.choose and the winMenu commands. What other such GUIisms are built into ** base ** R (I know about the tcltk package)? Or, better yet, how can I search on or list them? Many thanks. Bert Gunter Biometrics Research RY 84-16

R-Listers: A very minor -- and maybe silly -- question just for personal enlightenment. In S (either R or S-Plus, AFAIK) when one types or pastes a trellis graphics command into the commands/console window, the graph is automatically produced: e.g., trellis.device(...) xyplot(y~x) If one puts these in a function and calls the function, the same occurs. However, if one sources in these command

My apologies if these are known -- I'm new to R (moved over from S-Plus). All on Windows NT GUI, R1.6.1 and associated packages. 1. save(x) gives the following error message: Error in save(x) : `file' must be non-empty string According to the save() help file, the empty string is the default. 2. In the file>Display file GUI menu, if you try to display a file that is in use by

Hello everybody, In am trying to analyse a BACI experiment and I really want to do it with R (which I find really exciting). So, before moving on I though it would be a good idea to repeat some known experiments which are quite similar to my own. I tried to reproduce 2 published examples but without much success. The first one in particular is a published dataset analysed with SAS by

R1.6.2 winnt. file.choose() gives an error if the dialog is cancelled without choosing a file. This can be easily dealt with via try(), but I would have thought that a NULL or NA return would be the expected behavior. Cheers, Bert Gunter Biometrics Research RY 84-16 Merck & Company P.O. Box 2000 Rahway, NJ 07065-0900 Phone: (732) 594-7765 mailto: bert_gunter@merck.com "The business of

Dear R users, Firstly, I would like to congratulate the R core team in bringing out R 1.0.0 and all who have helped in developing it. I have been having problems with using se.contrasts and would be pleased if someone help. I have been doing a repeated measures ANOVA using aov using a split plot design for a single variable, color. The aov results were as follows: > summary(aov(CD2~cont +

I'm starting to understand fixed and random effects, but I'm puzzled a bit. Here is an example from Hays's textbook (which is great at explaining fixed vs. random effects, at least to dummies like me), from the section on mixed models. You need library(nlme) in order to run it. ------ task <- gl(3,2,36) # Three tasks, a fixed effect. subj <- gl(6,6,36) # Six subjects, a random

Dear List: Below is the validation output of a fitted ordinal logistic model using the bootstrap in the rms package. My interpretation is that most of the corrected indices indicate little overfitting, however the slope seems to indicate that the model is too optimistic. Given that most of the corrected indices seem reasonable, would it be appropriate to use this model on future data if the

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Hi, I posted this question a while back and didn't get much response. Since then, I've done a bit more experimenting and wonder if someone can help me move forward towards resolution. The orignal question... > I'm running Dovecot0.99.13 on Fedora Core 3 and things work fine when using either > Thunderbird 1.0 or Outlook Express as IMAP clients. Outlook (2002 SP3) on

I've posted the following to R-help on May 15. It has reproducible R code for real data -- and a real (academic, i.e unpaid) consultion background. I'd be glad for some insight here, mainly not for myself. In the mean time, we've learned that it is to be expected for anova(*, "marginal") to be contrast dependent, but still are glad for advice if you have experience. Thank