search for: vokey

...g the Error() partitioning, but can't find one that produces both the correct analysis *AND* no singularity error on the aov() call. Any suggestions? -- Please avoid sending me Word or PowerPoint attachments. See <http://www.gnu.org/philosophy/no-word-attachments.html> -Dr. John R. Vokey

R for OS X, version 2.0.1 Has the add parameter of plot commands been deprecated? It no longer occurs in the help listing for plot, and doesn't work, either. If it has been deprecated, what is the replacement? That is, how does one overlay an existing plot? -- John R. Vokey, PhD Professor B.E.R.G. - Behaviour and Evolution Research Group Micro-Cognition Laboratory Department of Psychology & Neuroscience University of Lethbridge Lethbridge, Alberta T1K 3M4 CANADA

...ke the latter? That is, in a data.frame, how does one indicate that a factor is an *ordered* factor such that contr.poly is invoked in the aov or lm call? -- Please avoid sending me Word or PowerPoint attachments. See <http://www.gnu.org/philosophy/no-word-attachments.html> -Dr. John R. Vokey

...computed the proportions, fixed the header, saved it as a text file, and the read it back into R to do the regressions. There has got to be an easier way. -- Please avoid sending me Word or PowerPoint attachments. See <http://www.gnu.org/philosophy/no-word-attachments.html> -Dr. John R. Vokey

Yes, I am a newbie at R, but it is not the complex commands in R that have me baffled, but simple data commands. For example, why does something like: > plot(Girth ~ Height) *not* work after a command that allegedly loads the data: > data(trees) with the error message: Error in eval(expr, envir, enclos) : Object "Girth" not found but does work after the command: >

..., in experiment "1", and of linelabel "al1". And any one cross only appears once in the dataset, so each horizontal line refers to a distinct cross, about which a single observation has been made. Is that the kind of information you were looking for? - David >From: John Vokey <vokey at uleth.ca> >To: dalelemu at hotmail.com >Subject: RE: [R] Trouble phrasing an R command that will run the model i > need (ANOVA, nested) >Date: Fri, 24 Mar 2006 09:41:49 -0700 > >David, > I could probably help you with aov(), but I need more information about...

...t as the vector IV and response (correct/ incorrect) as the vector DV. [The actual design is more complex, but this simple structure captures my concern.] -- Please avoid sending me Word or PowerPoint attachments. See <http://www.gnu.org/philosophy/no-word-attachments.html> -Dr. John R. Vokey

...remove all the list, uh, stuff (and ignoring the no doubt great pleasure to be had by chiming in to agree with my exalted twittedness), what does one do? -- Please avoid sending me Word or PowerPoint attachments. See <http://www.gnu.org/philosophy/no-word-attachments.html> -Dr. John R. Vokey

Dear All, when I'm running a PCA with prcomp(USArrests, scale = TRUE) I get the right principal components, but with the wrong sign infront Rotation: PC1 PC2 PC3 PC4 Murder 0.5358995 -0.4181809 0.3412327 0.64922780 Assault 0.5831836 -0.1879856 0.2681484 -0.74340748 UrbanPop 0.2781909 0.8728062 0.3780158 0.13387773 Rape 0.5434321 0.1673186 -0.8177779 0.08902432 instead of PC1 PC2 PC3 PC4

I need to create artificial datasets with specific correlation coefficients (i.e. a dataset that returns r = 0.30, etc.) as examples for a lab I am teaching this summer. Is there a way to do that in R? Thanks. Jim Milks Graduate Student Environmental Sciences Ph.D. Program 136 Biological Sciences Wright State University 3640 Colonel Glenn Hwy Dayton, OH 45435 [[alternative HTML version

Hi, I'm a new R user, coming from SPSS, and without a particularly strong stats background. I've got a data set that I'd like to do a mixed-design ANOVA with. No missing values. Here's the summary: summary(learnDat.ae) Type Subject idio struct TrainErrs cond 0:20 11 : 3 idio :28 ae :58 Min. : 0.00 idioae :28 2:19 12 : 3

Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a

Hello there, I have a problem concerning bootstrapping in R - especially focusing on the resampling part of it. I try to sum it up in a simplified way so that I would not confuse anybody. I have a small database consisting of 20 observations (basically numbers from 1 to 20, I mean: 1, 2, 3, 4, 5, ... 18, 19, 20). I would like to resample this database many times for the bootstrap process with

Dear list members: I have the following data: group <- rep(rep(1:2, c(5,5)), 3) time <- rep(1:3, rep(10,3)) subject <- rep(1:10, 3) p.pa <- c(92, 44, 49, 52, 41, 34, 32, 65, 47, 58, 94, 82, 48, 60, 47, 46, 41, 73, 60, 69, 95, 53, 44, 66, 62, 46, 53, 73, 84, 79) P.PA <- data.frame(subject, group, time, p.pa) The ten subjects were randomly assigned to one of two groups and measured