similar to: Help with lme basics

Hi all, I have a strange problem and rigth now I can't figure out a solution. Trying to calculate an ANOVA with one between subject factor (group) and one within (hemisphere). My dependent variable is source localization (data). My N = 25. My data.frame looks like this: > ML.dist.stack subj group hemisphere data 1 1 tin left 0.7460840 2 2 tin left

I have 2 questions on ANOVA with 1 between subjects factor and 2 within factors. 1. I am confused on how to do the analysis with aov because I have seen two examples on the web with different solutions. a) Jon Baron (http://www.psych.upenn.edu/~baron/rpsych/rpsych.html) does 6.8.5 Example 5: Stevens pp. 468 - 474 (one between, two within) between: gp within: drug, dose aov(effect ~ gp * drug *

thanks a lot Renaud. but i was interested in Finney's fiducial confidence intervals of LD50 so to obtain comparable results with SPSS. But your reply leads me to the next question: does anybody know what is the best method (asymptotic, bootstrap etc.) for calculating confidence intervals of LD50? i could "get rid" of Finney's fiducial confidence intervals but

Dear R-Helpers, Is there a way to draw shaded (filled) polygons in panel graphs produced by xyplot ? I made different trials (see below) with polygon() and grid.polygon() but polygons are not drawn (probably for the same reason that prevents the use of lines, points, etc. in xyplot panels). Thanks in advance, Renaud > Water id label longitude latitude 515 21 Zone inondable

I am working with Probit regression (I cannot switch to logit) can anybody help me in finding out how to obtain with R Finney's fiducial confidence intervals for the levels of the predictor (Dose) needed to produce a proportion of 50% of responses(LD50, ED50 etc.)? If the Pearson chi-square goodness-of-fit test is significant (by default), a heterogeneity factor should be used to calculate

Dear all, Has anyone written functions to compute (and ideally project / plot onto a plane) confidence ellipsoids for q linear model parameters, q > 2 ? Greetings and best wishes, Renaud -- Dr Renaud Lancelot, v?t?rinaire CIRAD, D?partement Elevage et M?decine V?t?rinaire (CIRAD-Emvt) Programme Productions Animales http://www.cirad.fr/presentation/programmes/prod-ani.shtml ISRA-LNERV

To Windows R users: The binary build of R that I uploaded on Tuesday contained errors in the compiled HTML help files and some of the PDF versions of the manuals. In particular, the index was missing from the CHM files, and the table of contents was missing from at least one of the manuals. I've since found the error in my setup, and have rebuilt the distribution. I uploaded it to CRAN

To Windows R users: The binary build of R that I uploaded on Tuesday contained errors in the compiled HTML help files and some of the PDF versions of the manuals. In particular, the index was missing from the CHM files, and the table of contents was missing from at least one of the manuals. I've since found the error in my setup, and have rebuilt the distribution. I uploaded it to CRAN

> version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 5.0 year 2002 month 04 day 29 language R OS Win98 I have problems to install some of the packages dowloaded from CRAN (whatever the

I met today a computer crash and our maintenance officer had to reinstall some components of the OS (MS Windows XP Pro) as well as the Internet browser (among other things). Now, I cannot install packages from a distant repository: > utils:::menuInstallPkgs() Error in .readRDS(pfile) : unknown input format > traceback() 5: .readRDS(pfile) 4: .packages(all.available = TRUE) 3:

Dear all, platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status Patched major 1 minor 5.0 year 2002 month 05 day 15 language R Is there a way to include a graph in a help file (Rd file processed with make pkg-mypkg) ? Thanks in advance, Renaud -- Dr

Dear all, I have computed a digital terrain model from a set of points (x, y, z) using the function interp() in package akima. I want to predict flooded surfaces given target values of z. I can display the flooded surfaces with contour() or image(), but I don't know how to get the polygons delimiting the surfaces. Did anyone write a function for this purpose ? Best regards, Renaud --

Dear all, I am trying to avoid the warnings produced by: > x <- -2:2 > log(x) [1] NaN NaN -Inf 0.0000000 0.6931472 Warning message: production de NaN in: log(x) I thought that using ifelse would be a solution, but it is not the case: > ifelse(test = x < 0, yes = NaN, no = log(x)) [1] NaN NaN -Inf 0.0000000 0.6931472 Warning message: production

Hi, lme() users, Can some one tell me how to do this. I model Orthodont with the same G for random variables, but different R{i}'s for boys and girls, so that I can get sigma1_square_hat for boys and sigma2_square_hat for girls. The model is Y{i}=X{i}beta + Z{i}b + e{i} b ~ iid N(0,G) and e{i} ~ iid N(0,R{i}) i=1,2 orth.lme <- lme(distance ~ Sex * age, data=Orthodont, random=~age|Subject,

Dear all, 1. How can I compute the intersecting area between 2 polygons ? 2. I have polygons with coordinates in decimal degrees (i.e. 13 deg 30 min = 13.5 decimal degrees). I want to compute their area and get the results in square meters or square kiometers. Can anyone give me a conversion coefficient or a pointer where I can find this information (sorry for this off topic question) ? Thanks

Sorry if this is obvious, but my S skills aren't great and I haven't been able to find it documented anywhere. I want to write a new function for use with lme objects; the function will simply calculate an ICC (aka "rho") for each level of a mixed-effects model. What I need for this is pretty simple: (c(var1..varn, residual)) / sum(c(var1..varn, residual)) where var1..varn

I have a number of plots that I'm trying to do using the lattice package, unfortunately, they involve Posix values. A small sample of the data is as follows: Time TC.1 <Snipped> 1 2003-04-24 13:29:15 26.61 2 2003-04-24 13:29:30 26.48 3 2003-04-24 13:30:00 26.53 4 2003-04-24 13:30:30 27.85 <Snipped> where str(data) `data.frame': 415 obs. of

Please, forgive my ignorance on statistics, but I have a rather simple question concerning AIC. Small values of AIC mean good fit of the model. How about negative values of AIC? Is a model with AIC=0.5 considered to have better fit than a model with AIC=-500? I couldn't find anything explaining this in the documentation or any elementary statistics textbook that I have at my disposal. Thanks

I've put up a build of the current R-patched (and updated recommended packages) for Windows at http://www.stats.ox.ac.uk/pub/bdr/RWin/Rpre/SetupRpatched.exe This should be able to rename files on Win 9x (unlike the mid-May build) and can build packages accessing Rblas.dll. As ever, this is less tested than an official release, in particular only on Windows XP, but ought to have fewer

Dear all, I've just downloaded R.12.0 from CRAN (http://cran.r-project.org/bin/windows/base/release.htm). I am unable to find RGUI.exe as well as Rterm.exe. Conversely to what is explained in readme.R.2.12.0: There are two versions of the R executable in R-2.12.0\bin\i386 (32-bit) or R-2.12.0\bin\x64 (64-bit). I can't find directories i386 or x64 in R-2.12.0\bin -- Renaud Lancelot EDEN