similar to: psychometric functions

Hi all, I thought I was not SUCH a nooby:) How can I reverse a sequence/ vector? i.e., turn X <- 3 5 4 2 6 5 4 3 6 Into X <- 6 3 4 5 6 2 4 5 3 I mean without looping and indexing. There should be a very easy solution, shouldn't it? Mario __________________________________________________________________ Mario Maiworm Biological Psychology and Neuropsychology University of Hamburg

Greetings! I have an issue with an R editor (namely Tinn-R). A few weeks ago all of a sudden the backspace, enter and direction keys were not working. I updated Tinn-R to the newest version but still no sollution. After this I tried reinstalling it (prior to that I removed Tinn-R and deleted all the "leftovers" manually) and still no change. In every other execution (e.g. when I save a

Dear R-Experts, I was wondering how to fit a cumulative gaussian to a set of empirical data using R. On the R website as well as in the mail archives, I found a lot of help on how to fit a normal density function to empirical data, but unfortunately no advice on how to obtain reasonable estimates of m and sd for a gaussian ogive function. Specifically, I have data from a psychometric function

Dear R-Listers, to measure the psychometric curve of pitch discrimination, one sequentially presents two tones of slightly different pitch to an observer (animal will do), and asks "which is higher". The pschometric curve is the fraction of correct responses plotted against the pitch difference. It passes through 50% (pure guessing) at zero and normally approaches 100% at large

Hi, What package would you recommend for analyzing the validity/reliability of multiple choice tests. Doing things such as classical test analysis, factor analysis, item response theory. I've used psychometric (item.exam), MiscPsycho (alpha.Summary), and ltm (rcor.test). MiscPsycho reported the numbers most similar to what I get in SPSS: corrected point biserial correlations,

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

Dear R-Community, I'm currently trying to find a way to conduct a meta-analysis in R. I would like to analyze data from mostly-cross-sectional survey-studies. The effect sizes would be correlations. The R packages "meta" and "rmeta" are, as far as I can see, set up for analysis with effect sizes for differences (i.e. comparison of the means/odds-ratios of experimental

Please can someone advise me how I can adjust correlations using bonferroni's correction? I am doing manny correlation tests as part of an investigation of the validity/reliability of a psychometric measure. Help would be so appreciated! Cheers, Louise

Dear users, In my psychometric test i have applied logistic regression on my data. My data consists of 50 predictors (22 continuous and 28 categorical) plus a binary response. Using glm(), stepAIC() i didn't get satisfactory result as misclassification rate is too high. I think categorical variables are responsible for this debacle. Some of them have more than 6 level (one has 10 level).

Dear all, Is anybody knows simple method for creation norm tables for psychological tests for several groups distinguished by sex and age? best regards, Krzysztof

Hi Everyone, I've got a question about data representation. I have some psychometric data with 5 scores for 15 different groups. I've been asked to show some kind of mean plots. The data below is the mean and SD for a given group, unfortunately my employer doesn't want me posting full datasets. :( The groups V,W,X,Y,Z are divided into Bottom, (B), Middle (M) and Top (T). An

I want the standard error associated with a correlation. I can calculate using cor & var, but am wondering if there are libraries that already provide this function. [[alternative HTML version deleted]]

Hi, is there any package (or source code snippet) that will evaluate the Frechet distance for curves represented as sets of points? Searching around only threw up references to a Frechet distribution. Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at psu.edu> <http://jijo.cjb.net> GPG Fingerprint: 0CCA 8EE2 2EEB 25E2 AB04 06F7 1BB9

Dear list: I'm hoping to tap in to the statistical expertise in the group, especially those familiar with simulation techniques. I'm finalizing a study where I obtain standard errors from two sources. The first source is a monte carlo simulation and the other source is an analytical model I have developed that appears to recover the standard errors from the simulation. All analysis are

Hi I am doing this sort of thing: POLY: > > obj = best.tune(svm, similarity ~., data = training, kernel = "polynomial") > summary(obj) Call: best.tune(svm, similarity ~ ., data = training, kernel = "polynomial") Parameters: SVM-Type: eps-regression SVM-Kernel: polynomial cost: 1 degree: 3 gamma: 0.04545455 coef.0: 0

Dear Professor Revelle and R-helpers, This is a two-part question: the first part is general, and the second is specific to the psych package. First question: In the past I've constructed composite variables from questionnaire data by using rowMeans(), and then correlating items with the scale using cor() as an informal check for "bad" items. Over the weekend I decided to take a

I'm trying to plot an extrapolated logistic sigmoid curve using glm(..., family=binomial) as follows, but neither the fitted() points or the predict()ed curve are plotting correctly: > year <- c(2003+(6/12), 2004+(2/12), 2004+(10/12), 2005+(4/12)) > percent <- c(0.31, 0.43, 0.47, 0.50) > plot(year, percent, xlim=c(2003, 2007), ylim=c(0, 1)) > lm <- lm(percent ~ year)

Dear Sir/Madam Hello I'm Ph.D student of psychometric at the university of Tehran.I use R version 1.8.1. I want to upgrade the R into higher version.I downloaded the latest version "R-1.9.0.tgz". Unfortunately I could not to upgrade the R. Could you tell me how I can to upgrade the R,please? Best regards Asghar Minaei ===== Yours...Asghar Minaei

Hi, I am using logistic regression to classify a binary psychometric data. using glm() and then predict.glm() i got the predicted odds ratio of the testing data. Next i am going to plot ROC curve for the analysis of my study. Now what i will do: 1. first select a cut-off (say 0.4) and classify the output of predict.glm() into {0,1} segment and then use it to draw ROC curve using ROCR package

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 -