similar to: ANOVA between & within variance

Hello. How can I compute the Bootstrap p-Value for a one- and two sided test, when I have a bootstrap sample of a statistic of 1000 for example? My hypothesis are for example: 1. Two-Sided: H0: mean=0 vs. H1: mean!=0 2. One Sided: H0: mean>=0 vs. H1: mean<0 I hope you can help me Thanks in advance Regards, Andreas

hi, I am running R 2.7.2 Windows - recently the GUI-windows (for example to "change directory" or "read in R-scripts") do not open - well, they open, but close down directly afterwards. I can't select a directory or file ... I tried re-installing R - same problem again. does anybody have an idea? thanks gregor -- Gregor Rolshausen PhD Student; University of

hello, I want to fit a curve to a simple x,y dataset - my problem is, that I want to fit it for the following term: n(1-e^x/y) - so I get the n constant for my data... can anyone help/comment on that? cheers, gregor

library(glmmADMB) #Example for glmm.admb data(epil2) glmm.admb(y~Base*trt+Age +Visit,random=~Visit,group="subject",data=epil2,family="nbinom") Gives: Error in glmm.admb(y ~ Base * trt + Age + Visit, random = ~Visit, group = "subject", : The function maximizer failed ****************** R version 2.4.1 RC (2006-12-14 r40181) powerpc-apple-darwin8.8.0 locale: C

Dear R-helpers, I was curious why the output of summary (and many other functions in R) does not add a separator between the name of a factor and the label of a level (e.g., in the example below, 'group Trt'). If the user had lower case labels (e.g., 'trt'), the output would be particularly hard to read. ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt

Dear r-helpers, Could you please help me solve the following problem: When I run require(AlgDesign) trt <- LETTERS[1:5] blk <- 10 trtblk <- 3 BIB <- optBlock(~., withinData = trt, blocksizes = rep(trtblk, blk)) In response to the last command, R complains: Error in optBlock(~., withinData = trt, blocksizes = rep(trtblk, blk)) : object ".Random.seed" not found The

Dear R users, how can I test, whether two correlations differ significantly. (I want to prove, that variables are correlated differently, depending on the group a person is in.) Greetings from Freiburg im Breisgau (Germany), Timo Stolz

Hi, Does anyone know how to do a coord_trans() in which the y-axis is tranformed into (for example) -1000/y? Thanks, _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road Charlottesville, VA 22903 Office: B011

Dear r-helpers, Does anyone have a straightforward example of putting together three unrelated (expect for a common y-axis) xyplot() figures in what would be in base graphics a par(mfrow = c(1, 3)) arrangement? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102

Hi, I would like to use the effect() function (actually a slightly modified version of it) on the output of the lmer() function in the lme4 package. But the effects package requires the nlme pacvkage, which is incompatible with lme4. Workaround? ______________________________________________ Professor Michael Kubovy University of Virginia Department of Psychology for mail add: for FedEx or

Dear R-helpers, How do I transform v <- c('insd-otsd', 'sppr-unsp') into c('insd--otsd', 'sppr--unsp') ? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road Charlottesville, VA 22903

df1 <- data.frame(a = LETTERS[1:2], b = LETTERS[3:4], c = 1:2) I am looking for an idiom that swaps the elements of df$a and df$b when (e.g.) df$c == 2, resulting in df2 <- data.frame(a = LETTERS[c(1, 4)], b = LETTERS[c(3, 2)], c = 1:2) _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA

Dear Friends, Here is an algorithm for finding concave hulls: http://get.dsi.uminho.pt/local/ Has anyone implemented such an algorithm in R? RSiteSearch('concave hull') didn't reveal one (I think). _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology Postal Address: P.O.Box 400400, Charlottesville, VA 22904-4400 Express Parcels

Dear r-helpers, xx <- c(0.000, 0.210, 0.714, 0.514, 1.000, 0.190, 0.590, 0.152) yy <- c(0.000, 0.265, 0.256, 0.521, 0.538, 0.761, 0.821, 1.000) aa <- c(19, 19, 19, 21, 19, 21, 21, 21) x0 <- xx[c(1, 1, 2, 2, 2, 3, 3, 4, 4, 4, 5, 6, 6, 7)] y0 <- yy[c(1, 1, 2, 2, 2, 3, 3, 4, 4, 4, 5, 6, 6, 7)] x1 <- xx[c(2, 3, 3, 4, 6, 4, 5, 5, 6, 7, 7, 7, 8, 8)] y1 <- yy[c(2, 3, 3, 4, 6, 4, 5,

Dear R-helpers, It is not clear to me how you get measurement.error SD when you have a single dataset, and it is not clear to me how sensitive SIMEX is to errors in the estimates of measurement error. Could someone please point me to the relevant literature? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400

What am I doing wrong? > install.packages("Hmisc") trying URL `http://cran.r-project.org/src/contrib/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 47565 bytes opened URL ================================================== downloaded 46Kb trying URL `http://cran.r-project.org/src/contrib/Hmisc_3.0-1.tar.gz' Content type `application/x-tar' length

I am using xYplot to plot data and CIs. How do I add several lines to the figure? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road Charlottesville, VA 22903 Office: B011 +1-434-982-4729 Lab: B019

How does one define PDFs as yet undefined in R, such as the ex- gaussian, the sum of two RVs, one exponential, one Gaussian? The PDF would then be the convolution of an exponential PDF, dexp(), and a normal, dnorm(). Kindly cc me in your reply to r-help. Thanks, _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400

hello. I have a question on the interpretation of a logistic model. is it helpful to exponentiate the coefficients (estimates)? I think I once read something about that, but I cannot remember where. if so, how would be the interpretation of the exp(estimate) ? would there be a change of the interpretation of the ANOVA table (or is the ANOVA table not really helpful at all?). thanks for your

Dear r-helpers, Can anyone suggest why lm() doesn't complain here: summary(osss.lm1 <- lm(logOdds ~ c.setSize %in% task, data = osss)) whereas in package:nlme (and in package:lme4) osss.lmL <- lmList(logOdds ~ c.setSize %in% task | subj, data = osss) # Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : # contrasts can be applied only to factors with 2 or more