search for: grm

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=",&qu...

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...

...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") mirt<-mirt(as.data.frame(pcmdat),1,itemtype="graded",constrain=list(1,5,9,13,17,21,25)) # I was assuming that a GRM with constrained discrimination parameter would equal a PCM cf<-as.data.frame(unlist(coef(mirt))) md1<-cf[c(2,6,10,14,18,22,26),] md2<-cf[c(3,7,11,15,19,23,27),] md3<-cf[c(4,8,12,16,20,24,NA),] mirt<-as.data.frame(cbind(md1,md2,md3)) mirt[7,3]<-0.5*rowSums(mirt[7,1:2])#to get the...

I had an open session working in R and I regularly save the image with save.image(). However, after a period of inactivity of a few days. I quit the session. Now, when I try to restart R and load the same image I get the following result: > load("y:/grm/sdata/.rdata1") Error in load("y:/grm/sdata/.rdata1") : an xdr real data read error occured Can someone explain the cause of this? I hope this is not the end of it because it would set me back quite a while in recreating the objects. The image file is about 25MB. I'm using R 1.2...

...n items. In particular, two types of common item equating are included: alternate form equating (where common and unique items are analyzed simultaneously) and across sample equating (where different sets of unique items are analyzed separately based on previously calibrated anchor items). * grm() now works with the available cases when incomplete data (i.e., in the presence of NAs) are analyzed. * better algorithms, for Missing At Random missing data mechanisms, have been written for grm(), ltm(), rasch() and tpm(). * a residuals() method has been added for `grm', `ltm', `...

...n items. In particular, two types of common item equating are included: alternate form equating (where common and unique items are analyzed simultaneously) and across sample equating (where different sets of unique items are analyzed separately based on previously calibrated anchor items). * grm() now works with the available cases when incomplete data (i.e., in the presence of NAs) are analyzed. * better algorithms, for Missing At Random missing data mechanisms, have been written for grm(), ltm(), rasch() and tpm(). * a residuals() method has been added for `grm', `ltm', `...

...it all, and I'm not able to change cd. Supermount is not an option here, since there is no patch for later 2.4.X kernels. So any other way to get around that? If anyone would like to help me, I would be VERY grateful! Thank you in advance! --- Rune Elvemo --- Octagon / Digital Minds relvemo@grm.hia.no http://home.c2i.net/elvemo

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 be done? I can, of course, create a list,...

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 'rasch' is the possibility to plo...

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 'rasch' is the possibility to plo...

...'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 handle mix of dichotomous and polytomous items. * descript() returns more output, especially for dichotomous manifest variables. For more details check the CHANGES file. Future plans include development of functions for goodness-of-fit, and the Partial Credit Model. Any kind of feed...

...'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 handle mix of dichotomous and polytomous items. * descript() returns more output, especially for dichotomous manifest variables. For more details check the CHANGES file. Future plans include development of functions for goodness-of-fit, and the Partial Credit Model. Any kind of feed...

Hi: I have been working in Item Response Theory, exactly, with Nominal Response Model (NRM). Exist in R a function for estimate parameter and ability from database for this Model?. Thank you, Xavier G. Ordóñez [[alternative HTML version deleted]]

I have used R a lot in the past, but never for simulation. I have a code in SAS for the Graded Response Model (GRM), also known as Samejima's model. This code simulates an ordinal response, provided item characteristics (A=item discrimination, BB(G) are thresholds between various categorical responses). It is a macro file. I am thinking that I can write this as a function, and call it up inside a simulat...

Hello, I have configured Dovecot to work perfectly on Thundrebird using SSL certificates with STARTTLS on port 110. When I try to add this account on Gmail I get the error: Nov 16 14:04:17 mail dovecot: auth: Debug: auth client connected (pid=31587) Nov 16 14:04:17 mail dovecot: pop3-login: Disconnected (no auth attempts in 0 secs): user=<>, rip=209.85.160.136, lip=192.168.100.94,

...39;. Parameters should be formatted as either an object of class 'irt.pars' with multiple groups, a set of 'irt.pars' objects, or a set of 'sep.pars' objects. Once in this format, response probabilities can be computed using the functions 'drm', 'gpcm', 'grm', 'mcm', or 'nrm' or linking constants can be computed using 'plink'. The functions 'as.irt.pars', 'sep.pars', and 'combine.pars' can be used to create the 'irt.pars' and 'sep.pars' objects. 'summary' can be used to summar...

...39;. Parameters should be formatted as either an object of class 'irt.pars' with multiple groups, a set of 'irt.pars' objects, or a set of 'sep.pars' objects. Once in this format, response probabilities can be computed using the functions 'drm', 'gpcm', 'grm', 'mcm', or 'nrm' or linking constants can be computed using 'plink'. The functions 'as.irt.pars', 'sep.pars', and 'combine.pars' can be used to create the 'irt.pars' and 'sep.pars' objects. 'summary' can be used to summar...

.... Once this object has been created, the function 'plink' is used to estimate the linking constants and rescale item and/or ability parameters. In addition to the estimation of linking constants, response probabilities can be computed using the functions 'drm', 'gpcm', 'grm', 'mcm', or 'nrm' (for both unidimensional and multidimensional models). I am currently working on a step-by-step walk through of the package, but for now the current documentation contains extensive details and examples. The best documentation to start with is help(as.irt.pars...

.... Once this object has been created, the function 'plink' is used to estimate the linking constants and rescale item and/or ability parameters. In addition to the estimation of linking constants, response probabilities can be computed using the functions 'drm', 'gpcm', 'grm', 'mcm', or 'nrm' (for both unidimensional and multidimensional models). I am currently working on a step-by-step walk through of the package, but for now the current documentation contains extensive details and examples. The best documentation to start with is help(as.irt.pars...

...st shell reply 0 debug1: session_by_channel: session 0 channel 0 debug1: session_input_channel_req: session 0 req shell debug1: X11 connection requested. debug1: channel 2: new [X11 connection from 127.0.0.1 port 55536] debug1: channel 2: free: X11 connection from 127.0.0.1 port 55536, nchannels 3 grm at TEST_CLIENT ~ $ ssh -CXvvv bes at remotehost OpenSSH_3.9p1, OpenSSL 0.9.7d 17 Mar 2004 debug2: ssh_connect: needpriv 0 debug1: Connecting to remotehost [remotehost] port 22. debug1: Connection established. debug1: identity file /cygdrive/h/.ssh/identity type -1 debug1: identity file /cygdrive/h/...