Displaying 20 results from an estimated 1000 matches similar to: "package ltm -- version 0.8-0"
2006 Mar 13
0
package ltm -- version 0.4-0
Dear R-users,
I'd like to announce the new version of package 'ltm' for Item
Response Theory analysis. The function grm() (along with supporting
methods, i.e., anova, margins, factor.scores, etc.) has been added for
fitting the Graded Response Model for ordinal polytomous manifest
variables. An extra feature of the plot method for classes 'grm',
'ltm' and
2006 Mar 13
0
package ltm -- version 0.4-0
Dear R-users,
I'd like to announce the new version of package 'ltm' for Item
Response Theory analysis. The function grm() (along with supporting
methods, i.e., anova, margins, factor.scores, etc.) has been added for
fitting the Graded Response Model for ordinal polytomous manifest
variables. An extra feature of the plot method for classes 'grm',
'ltm' and
2012 Nov 08
0
mirt vs. eRm vs. ltm vs. winsteps
Dear R-List,
I tried to fit a partial credit model using the "pcmdat" from eRm-package comparing the results of mirt, eRm, ltm and winsteps.
The results where quite different, though. I cannot figure out what went wrong and I do not know which result I can rely on.
This is what I did in R
library(mirt)
#load(file="u3.RData")
2011 Aug 12
0
testEquatingData (part of ltm package) changes order of columns
Dear R community,
I hope someone is out there who has some insights into the ltm package.
Specifically, I am seeking help for the testEquatingData function which is
part of this package.
Here is an example of my data:
#install.packages("ltm", dependencies = TRUE)
library(ltm)
anchor<- as.data.frame(cbind(c(NA, NA, NA, NA, 1), c(NA, NA, NA, 1, NA),
c(1,1,NA,NA,NA)))
names(anchor)
2009 Oct 14
1
ltm package error for grm (IRT)
Using the grm function (graded response IRT model) in the ltm package I
receive the following error:
Error: subscript out of bounds
for several scales I'd like to examine. Here's a small example that if run a
few times will likley produce the error at least once
ch<-array(round(runif(50,1,5)),c(10,5))
grm(ch,start.val="random")
## or
2005 Sep 27
0
package 'ltm' -- version: 0.3-0
Dear R users,
I'd like to announce the new version of the package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch and
two-parameter logistic models) under the Item Response Theory
approach. Three main extra features have been added: (i) now both
ltm() and rasch() permit general fixed-value constraints (e.g., useful
for scaling purposes), (ii)
2005 Sep 27
0
package 'ltm' -- version: 0.3-0
Dear R users,
I'd like to announce the new version of the package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch and
two-parameter logistic models) under the Item Response Theory
approach. Three main extra features have been added: (i) now both
ltm() and rasch() permit general fixed-value constraints (e.g., useful
for scaling purposes), (ii)
2009 Mar 02
0
package ltm -- version 0.9-0
Dear R-users,
I'd like to announce the release of the new version of package 'ltm'
(i.e., ltm_0.9-0 soon available from CRAN) for Item Response Theory
analyses. This package provides a flexible framework for analyzing
dichotomous and polytomous data under various IRT models. Furthermore,
supporting functions for descriptive statistics, goodness-of-fit,
ability estimation and
2009 Mar 02
0
package ltm -- version 0.9-0
Dear R-users,
I'd like to announce the release of the new version of package 'ltm'
(i.e., ltm_0.9-0 soon available from CRAN) for Item Response Theory
analyses. This package provides a flexible framework for analyzing
dichotomous and polytomous data under various IRT models. Furthermore,
supporting functions for descriptive statistics, goodness-of-fit,
ability estimation and
2006 Sep 06
0
package ltm -- version 0.6-0
Dear R-users,
I'd like to announce the release of the new version of package 'ltm'
for analyzing multivariate dichotomous and polytomous data under the
Item Response Theory approach.
New features:
* function tpm() (along with supporting methods, i.e., anova, plot,
margins, factor.scores, etc.) has been added for fitting Birnbaum's
Three Parameter Model.
* grm() can now
2006 Sep 06
0
package ltm -- version 0.6-0
Dear R-users,
I'd like to announce the release of the new version of package 'ltm'
for analyzing multivariate dichotomous and polytomous data under the
Item Response Theory approach.
New features:
* function tpm() (along with supporting methods, i.e., anova, plot,
margins, factor.scores, etc.) has been added for fitting Birnbaum's
Three Parameter Model.
* grm() can now
2011 Jul 27
1
Inserting weights in ltm package
Afternoon R help,
I want to run Rasch/IRT analyses using the ltm package, however, I am
using large scale survey data which requires weighting for accurate
results. I attempted to create a weighted object to insert into the
formulae of the ltm packages, however, the survey data only includes
30 replicate weights and a sampling weight. The svrepdesign requires
additional information such as
2010 Mar 20
0
Getting a complete vector of Theta estimates from Package LTM
I am using package LTM to estimate a Rasch model:
irtestimates <- rasch(binRasch)
I want to get a single vector containing theta estimates for all the
rows (individuals) in my data matrix (hopefully in the same order as
my data matrix) such that the length of the theta vector = the number
of rows (participants) in my data matrix. I am using:
theta.est <-
2007 Jan 19
1
ability estimate with GRM of IRT
Hi my friends,
I have an issue with ability estimates when running GRM of IRT. I
have responses from 242 subjects but got 183 ability estimates.
Below is what I did to get the estimates.
1) I have a csv file "P1.csv" and I imported it into R and loaded
the "ltm" package by doing:
p1<-read.table("P1.csv",header=TRUE,sep=",")
library(ltm)
2) I
2011 Nov 20
2
ltm: Simplified approach to bootstrapping 2PL-Models?
Dear R-List,
to assess the model fit for 2PL-models, I tried to mimic the
bootstrap-approach chosen in the GoF.rasch()-function. Not being a
statistician, I was wondering whether the following simplification
(omit the "chi-squared-expressed model fit-step") would be appropriate:
GoF.ltm <- function(object, B = 50, ...){
liFits <- list()
for(i in 1:B){
rndDat <-
2011 Feb 10
1
factor.scores
The function factor.scores is used with package ltm and others to estimate IRT type scores for various models. It inherits objects of class grm, gpcm and a few others. What I would like to do is to use the factor.scores function, but feed it my own item parameters (from a bifactor model where the 2PL parameters are adjusted for the bifactor structure). Does anybody have an idea of how this might
2007 Apr 27
0
Protocol for data inclusion in new packages
In the near future I will release MiscPsycho, a package that contains
various functions useful for applied psychometricians. I would like to
include some data sets for distribution in the package, but have not
created any of these on my own, but have used data distributed in other
packages such as the LSAT data in the ltm package.
Is it appropriate for me to distribute a data set in the package I
2008 Mar 10
1
ltm package question
Hello All,
I was wondering how I can get the overall Pearson chi^2 test of model fit
with its df and p value in the LTM package for the 2PL models.
Thanks,
--
Davood Tofighi
Department of Psychology
Arizona State University
[[alternative HTML version deleted]]
2008 Sep 18
2
Ability estimates for partial credit model
Dear all,
I'm working on ability estimates using Rasch model. Using the "ltm"
package, the procedure is quite simple:
## Factor Scores for the Rasch model
fit <- rasch(LSAT)
factor.scores(fit)
What about Partial Credit Model (PCM)? For PCM I use PCM function from
eRm package. Is there any similar function like factor.scores to
estimate ability scores using PCM model?
Best,
2008 Feb 28
0
problem with the ltm package - 3PL model
Hi Xavier,
the reason you observe this feature is that in the 'constraint'
argument you should specify the values under the additive
parameterization, i.e., when in the second column of the matrix
supplied in 'constraint' you specify 2, then you need to provide the
easiness parameters (not the difficulty parameters) in the third
column. Check the Details section of ?tpm() and