search for: unidimensional

I was wondering if someone could point in the direction of a package that could generate not heatmaps, but something like a unidimensional heat map. I might be mistaken, but it seems like image and heatmap are an overkill for such a simple task. For example, if I have a data frame: x<-data.frame(myname=paste("value",1:10,sep=""),a=1:10,b=sample(1:10,10,replace=T)) I'd like to create a chart (it's more...

I'm trying to put together an R routine to conduct unidimensional unfolding scaling analysis using maximum likelihood. My problem is that ML optimization will get stuck at latent scale points that are far from optimal. The point optimizes on one of the observed variables but not others and for ML to move away from this 'local optimum', it has to move in...

An updated version of the package plink has been uploaded to CRAN. This is a major revision that now includes multidimensional models and methods. plink is a package for conducting unidimensional and multidimensional IRT-based test linking using separate calibration methods for multiple groups for single-format or mixed-format common items. The package supports sixteen IRT models and eleven calibration methods. Dichotomous Models: 1PL, 2PL, 3PL, M1PL, M2PL, M3PL Polytomous Models: -Graded...

An updated version of the package plink has been uploaded to CRAN. This is a major revision that now includes multidimensional models and methods. plink is a package for conducting unidimensional and multidimensional IRT-based test linking using separate calibration methods for multiple groups for single-format or mixed-format common items. The package supports sixteen IRT models and eleven calibration methods. Dichotomous Models: 1PL, 2PL, 3PL, M1PL, M2PL, M3PL Polytomous Models: -Graded...

...xt step of the forward search. I don't understand what I can do to remedy this error. The data are dichotomized (1,0) respsonses from a multiple-choice exam that 150 students have completed. If I run the entire test (37 items) , the fwd.msa algorithm works fine. However, the entire test is not unidimensional, so I want to perform separate analyses with the several unidimensional scales comprised by the entire test. Yet when I select those 4-5 item scales, I run into this error. Any ideas how to proceed? The data are 150 responses to a 37 item test. For the first 15 items, they look like this (the va...

Dear R community, I was trying to estimate density at point zero of a multivariate distribution (9 dimensions) and for this I was using a multinormal approximation and the function dmvnorm , gtools package. To have a sense of the error I tried to look the mismatch between a unidimensional version of my distribution and estimate density at point zero with function density, dmvnorm and dnorm. At my big surprise dmvnorm and dnorm give very different result and dmvnorm match even better the theoritical distribution than the function density. How come? #sampling from triangular distr...

Alternatively, just type debug(optim) before using it, then step through it by hitting enter repeatedly... When you're done, do undebug(optim). Andy > From: Spencer Graves > > Have you looked at the code for "optim"? If you > execute "optim", it > will list the code. You can copy that into a script file and walk > through it line by line to

...:30]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... This breaks: > cov(x) [,1] [1,] 0.9600812 > cov(x[20:30]) Erreur dans cov(x[20:30]) : fournir 'x' et 'y' ou bien 'x' en matrice And this behavior is braking function clustIndex (when used with unidimensional data), from the package cclust, file Rindexes.R, lines 137-147: ttww <- function(x, clsize, cluster) { n <- sum(clsize) k <- length(clsize) w<-0 tt <- cov(x)*n for (l in 1:k) w<- w+cov(x[cluster==l,])*clsize[l]...

dear R experts--- I have (many) unidimensional root problems. think loc.of.root <- uniroot( f= function(x,a) log( exp(a) + a) + a, c(.,9e10), a=rnorm(1) ) $root (for some coefficients a, there won't be a solution; for others, it may exceed the domain. implied volatilities in various Black-Scholes formulas and variant formulas are l...

Estimados una consulta me encuentro graficando un histograma cuyos datos no provienen de una distribución clásica como la normal exponenial, poisson, etc, Lo que necesito es colocar una curva no paramétrica que permita evidenciar el ajuste de los datos a esa curva ya que son muchos (alrededor de 80000). Muchas gracias [[alternative HTML version deleted]]

..., loess, or kernel). 'ask': interactive turning over of plots can be switched off (only useful if automated figure export is in effect, e.g., when using Sweave). - simulation module for 0-1 response matrices: sim.rasch() for Rasch homogeneous data, sim.2pl() for 2-PL data, sim.xdim() for unidimensionality violation, and sim.locdep() for locally dependent item responses. - package vignette "eRmvig" added. Best, Patrick _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages

...t is some sort of simulation/bootstrapping, which should be straightforward enough if I use just the first rank to denote "most important"... but that seems to ignore the information contained in the lower ranks. My next thought is that I should attempt some form of ordination .. some unidimensional scaling using perhaps a 1 dimensional cmdscale solution .. this rests on the ability to build a suitable distance matrix, which I think is possible. Or maybe a form of Thurstone scaling. If I wrapped this in the function called by boot .. a unique ordination solution for each sample draw, mappe...

..., loess, or kernel). 'ask': interactive turning over of plots can be switched off (only useful if automated figure export is in effect, e.g., when using Sweave). - simulation module for 0-1 response matrices: sim.rasch() for Rasch homogeneous data, sim.2pl() for 2-PL data, sim.xdim() for unidimensionality violation, and sim.locdep() for locally dependent item responses. - package vignette "eRmvig" added. Best, Patrick _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages

...items in 43 individuals with possible scores 0,1,2,3. Attempting either a PCM or RSM model fit simply hangs - no error messages but no return to command prompt and a continuously spinning "work in progress" indicator. The scores are from an instrument whose relevant psychometrics (e.g unidimensionality) have been established in other clinical populations: I'm studying a new disease group. I strongly suspect the problem relates to undesirable properties of the dataset: a significant missing data rate (about 20%) and a rather uneven distribution amongst the possible scores with relative pauc...

...de: * The new functions person.fit() and item.fit() compute p-values for person- and item-fit statistics for IRT models for dichotomous data. The `simulate.p.value' argument enables the computation of p-values based on a Monte Carlo procedure. * The new function unidimTest() checks the unidimensionality assumption for dichotomous data IRT models, using a Modified Parallel Analysis. * The new function testEquatingData() prepares data-sets for test equating by common items. In particular, two types of common item equating are included: alternate form equating (where common and unique item...

...de: * The new functions person.fit() and item.fit() compute p-values for person- and item-fit statistics for IRT models for dichotomous data. The `simulate.p.value' argument enables the computation of p-values based on a Monte Carlo procedure. * The new function unidimTest() checks the unidimensionality assumption for dichotomous data IRT models, using a Modified Parallel Analysis. * The new function testEquatingData() prepares data-sets for test equating by common items. In particular, two types of common item equating are included: alternate form equating (where common and unique item...

The first version of the package plink has been uploaded to CRAN. plink is a package for conducting unidimensional IRT scaling and chain linking for multiple groups for single-format or mixed-format common items. The package supports eight IRT models and four calibration methods. Dichotomous Models: 1PL, 2PL, 3PL Polytomous Models: -Graded response model -Partial credit model -Generalized partial credit model...

The first version of the package plink has been uploaded to CRAN. plink is a package for conducting unidimensional IRT scaling and chain linking for multiple groups for single-format or mixed-format common items. The package supports eight IRT models and four calibration methods. Dichotomous Models: 1PL, 2PL, 3PL Polytomous Models: -Graded response model -Partial credit model -Generalized partial credit model...

...aro? XD Un saludo, Isidro De: Olivier Nuñez [mailto:onunez en unex.es] Enviado el: martes, 30 de septiembre de 2014 15:23 Para: jluis gilsanz CC: ihidalgo en jccm.es; r-help-es en r-project.org Asunto: Re: [R-es] Clasificacion de individuos Me parece que tu ordenación es esencialmente unidimensional. Por lo tanto, en algún momento tendrás que considerar una combinación de tus tres variables. Ignoro el contexto, pero la ponderación de cada una debería ser conforme a los criterios de la empresa que evalúa al personal. Una vez tengas tu variable podrás definir los tres grupos con la función c...

Hola Isidro: También había sopesado esa posibilidad pero por una parte me parecía "complicar" el proceso y por otra tengo mis dudas acerca de que en que el análisis cluster pueda prescindir de la hipótesis de Normalidad en las dos variables "raras" que tengo. De cualquier forma muchas gracias por tu idea. Un saludo {In Archive} RE: [R-es] Clasificacion de