similar to: new package 'randomLCA'

Can anybody, please, explain me how many parameter are estimated using randomLCA? For examples, model "dentistry.lca2random" estimate 1 scale (or variance, b_j) parameter and 2 position parameters (a_cj)? Doesn't it? Do I need at least 4 diagnostic tests for such a model? What happens if I specify options blocksize and byclass? How many diagnostic tests (or rater) I need?

It seems like the Bayesian folks like to hide. Hey, I just want to get the job done whether using frequency or Bayesian stats. Can anybody suggest a good introduction to Bayesian Analysis? ----- Forwarded message from Ken Beath <kjbeath at kagi.com> ----- To: Joshua N Pritikin <jpritikin at pobox.com> From: Ken Beath <kjbeath at kagi.com> Subject: Remedial stats Hi,

Please can someone explain to me how to use randomLCA in R for an analysis. I tried using it and had this error (copied below) which indicated my patterns must consist of 0 or 1. I assume I am doing something wrong. Please help. > library(lattice) > library(boot) Attaching package: ‘boot’ The following object(s) are masked from ‘package:lattice’: melanoma > library(utils) >

What's the best approach to running latent class analysis with R? I've downloaded both randomLCA and poLCA packages, but I am interesting in running a standard LCA with individual records (not frequency table) as input data. Wen Gu John Jay College of Criminal Justice445 West 59 StreetNew York, NY 10029 wgu@gc.cuny.edu _________________________________________________________________

_____ De : Pousset [mailto:maud.pousset@noos.fr] Envoyé : mardi 4 juillet 2006 18:38 À : 'r-help@stat.math.ethz.ch' Objet : Latent Class Analysis Hello everybody, I am working on latent class analysis and have already used the ‘R’ function « lca » (in the e1071 package). I ‘ve got interesting results but I can’t simply find out the methodology used by this routine : 1) What

Dear UseRs! We are pleased to announce the release of our new package 'PVAClone'. The 'PVAClone' package implements Population Viability Analysis (PVA) methodology using data cloning. The data cloning algorithm by Lele et al. (2007, 2010) is employed to compute maximum likelihood estimates of the state-space model parameters and the corresponding standard errors, heavily

Dear R-users, I'd like to announce the release of my new package "ltm" (available from CRAN), for fitting Latent Trait Models (including the Rasch model) under the Item Response Theory approach. The latent trait model is the analogous of the factor analysis model for Bernoulli response data. "ltm" fits the linear one- and two-factor models but also allows for

Dear R users, I would like to perform Latent Class Logit Models for the analysis of choice experiments in environmental valuation. This kind of analysis is usually performed with NLogit Software (http://www.limdep.com). I attach the results I usually obtain using NLogit and NLogit model specifications. For Random parameter models and Logit Models I usually perform my analysis with the package

Dear all, I am pleased to announce the release of a new package named 'clusterMI' on CRAN. clusterMI allows clustering of incomplete observations by addressing missing values using multiple imputation. For achieving this goal, the methodology consists in three steps: 1. missing data imputation using tailored imputation models: four multiple imputation methods are proposed, two are

Maybe you want to check out the prevalence package (http://cran.r-project.org/web/packages/prevalence/index.html), and its development version on GitHub (https://github.com/brechtdv/prevalence/). When you have two tests, and neither can be considered to be a 'gold standard' (ie, SE & SP = 100%), Bayesian latent class approaches can help you to estimate true prevalence, sensitivity

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

I have just uploaded an updated version of my boolean package (v1.05), which should be propagating through CRAN's mirrors soon. Boolean permits estimation of Boolean logit and probit models (see Braumoeller (2003), full reference in help file, for derivation). Boolean logit and probit are a family of partial-observability n-variate models designed to permit researchers to model causal

Hello useRs, MBESS (Methods for the Behavioral, Educational, and Social Sciences) has recently been released and should be on all of the mirrors by now (with binaries for Mac and Windows: http://cran.r-project.org/src/contrib/Descriptions/MBESS.html). The major contribution of MBESS is confidence intervals for noncentrality parameters (t, F, and chi-square) and standardized effect sizes (e.g.,

Dear R-users, I'd like to announce the release of the new version of package `ltm' (i.e., ltm_0.8-0 soon available from CRAN) for Item Response Theory analyses. This package provides a flexible framework for analyzing dichotomous and polytomous data under IRT, including the Rasch model, the Two-Parameter Logistic model, Birnbaum's Three-Parameter model, the Latent Trait model

Dear UseRs! We are pleased to announce the release of our new package 'PVAClone'. The 'PVAClone' package implements Population Viability Analysis (PVA) methodology using data cloning. The data cloning algorithm by Lele et al. (2007, 2010) is employed to compute maximum likelihood estimates of the state-space model parameters and the corresponding standard errors, heavily

CRAN (and crantastic) updates this week New packages ------------ * apcluster (1.0.1) Ulrich Bodenhofer http://crantastic.org/packages/apcluster The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The algorithms are analogous to the Matlab code published by Frey and Dueck. * BioPhysConnectoR (1.6-1) Franziska Hoffgaard

[ Not sure why, but the first time I sent this it never seemed to go through; apologies if you're seeing this twice ... ] I have some fully functional code that I'm guessing can be done better/quicker with some savvy R vector tricks; any help to make this run a bit faster would be greatly appreciated; I'm particularly stuck on how to calculate using "row-wise" vectors

Dear R-users, A new version of `lavaan' (for latent variable analysis) is now available on CRAN. The current version of lavaan (0.4-8) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org To get a first impression of how the 'lavaan model syntax' looks

Package news (see below for general description of functionality) depmixS4 version 1.3-0 has been released on CRAN. See the NEWS file for an overview of all changes. The most important user-visible changes are: 1) more compact pretty-printing of parameters in print/summary of (dep)mix objects (following lm/glm style of presenting results) 2) some speed improvements in the EM algorithm, most

- This mail is in HTML. Some elements may be ommited in plain text. - WorldCIST Conference WorldCIST'15 - 3rd World Conference on Information Systems and Technologies, to be held at Ponta Delgada, S?o Miguel, Azores, Portugal, 1 - 3 April 2015, is a global forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences and concerns in