similar to: Random Bernoulli sequences with given point-biserial correlation?

Hello, I found in the forum two threads about point biserial correlation. One of them (1) mentioned "a point-biserial correlation is just a Pearson correlation where one of the variables is dichotomous. Thus, the command is just the normal cor function". The other (2) mentioned "Professor Fox's package polycor" as a way to calculate point biserial correlation?

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

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

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

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

Dear list, has anyone written a package/function in R for computing a point- biserial resp. biserial correlation? Thanks in advance Bernd

hi, is there an option to calculate the 'within' & 'between' group variances for a simple ANOVA (aov) model (2 groups, 1 trait, normally distr.) ? or do I have to calculate them from the Sum Sq ? thanks for your time and greetings, gregor -- Gregor Rolshausen PhD Student; University of Freiburg, Germany e-mail: gregor.rolshausen at biologie.uni-freiburg.de tel. :

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

Dear R-helpers, I need to generate all the binary sequences of length n (here n = 8) that start with 1 and have no fewer than two of each digit, and are not cyclic permutations of each other. Here is what I have done: len <- 8 df <- as.data.frame(numeric(2^(len - 1)) %o% numeric(len)) require(partitions) for (i in 1:2^(len - 1)) df[i, ] <- binary(i, dim = len)[[1]] df <-

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

Dear Friends, I not sure whether this is an Sweave or a beamer problem. The Rnw file: \documentclass[compress,smaller]{beamer} %\documentclass{article} %\usepackage{beamerarticle} \usepackage{Sweave} \title{Psychophysics II} \date{September 9, 2008} \begin{document} \frame{ \begin{Schunk} \begin{Sinput} > ro <- 0.2 > c <- seq(from = -3, to = 4, by = 0.1) > fn <- 1 -

Dear R-users, I'm running a lmer model using the lme4 package. My dependent variable is dichotomous and I'm using the "binomial" family. The results are slightly different from the HLM results based on a Bernoulli distribution. I read that a Bernoulli distribution is an extension of a binomial distribution. Is that right? If so, how can I adapt my R model to a Bernoulli

Dear R-helpers, I have an xyplot of the following kind: xYplot(y ~ x | p, groups = factor(gg, levels = c('1', '5', '2', '4', '3')), strip = strip.custom(var.name = 'g', factor.levels = c(1', '5', '2', '4', '3'), strip.levels = T, strip.names = T, sep = ' = ', shingle.intervals = NULL), data =