search for: lsat

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]]

Dear Listers: I used cronbach{psy} to evaluate the internal consistency and some set of variables gave me alpha=-1.1003, while other, alpha=-0.2; alpha=0.89; and so on. I am interested in knowing how to interpret 1. negative value 2. negative value less than -1. I also want to re-mention my previous question about how to evaluate the consistency of a set of variables and about the total

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, Andrej

Hello, I will use the lca method in the e1071 package. But I get the following error: Error in pas[j, ] <- drop(exp(rep(1, nvar) %*% log(mp))) : number of items to replace is not a multiple of replacement length Does anybody know this error and knows what this means? Kind regards, Tryntsje

...s horizontales en los valores de 0.25, 0.50 y 0.75. Me gustaría que en el gráfico, desaparezcan las marcas de 0,.2, 0.4, 0.6 y 0.8 y aparezcan en 0.25, 0.50 y 0.75. He probado varias cosas que he visto por Googe pero no me han funcionado. ¿Alguna idea? library(ltm) # creo el modelo modelo <- ltm(LSAT ~ z1) # represento el modelo plot(modelo, legend = TRUE, cx = "bottomright", lwd = 3,cex.main = 1.5, cex.lab = 1.3, cex = 1.1,main="") # creamos las líneas horizontales abline(h=0.25, col="purple") abline(h=0.50, col="red") abline(h=0.75, col="green&quot...

Hola a todos, Os envío una consulta que considero sencilla pero me está resultando imposible de resolver. Si ejecutáis el siguiente código, obtendréis la gráfica que os adjunto: library(ltm) modelo <- rasch(LSAT) plot(modelo, main="Curva probabilidad pregunta 1",legend = TRUE, cx = "bottomright", items=1,xlab="Conocimiento",ylab="Probabilidad") Resulta que la gráfica saca una leyenda que dice "ítem 1". Querría eliminarla. Resulta que si en legend hago = FAL...

Hi R users, I have one simple question but I really don't know why I can't get it work. The data was adopted from Efron's An introduction to the bootstrap book. > nlaw LSAT GPA [1,] 576 3.39 [2,] 635 3.30 [3,] 558 2.81 [4,] 578 3.03 [5,] 666 3.44 [6,] 580 3.07 [7,] 555 3.00 [8,] 661 3.43 [9,] 651 3.36 [10,] 605 3.13 [11,] 653 3.12 [12,] 575 2.74 [13,] 545 2.76 [14,] 572 2.88 [15,] 594 2.96 > nlaw<-as.matrix(law[,-1]) > corr.t...

..., 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 the following for an illustration: library(ltm) fit <- tpm(LSAT) cf <- coef(fit) constr <- rbind( cbind(1:3, c(1,1,1), cf[1:3, 1]), cbind(1:3, c(3,3,3), cf[1:3, 3]), cbind(1:3, c(2,2,2), - cf[1:3, 2] * cf[1:3, 3]) ) fit2 <- tpm(LSAT, constraint = constr) coef(fit)[1:3, ] coef(fit2)[1:3, ] I hope it's more clear now. Best, Dimitris...

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 <-

...s horizontales en los valores de 0.25, 0.50 y 0.75. Me gustaría que en el gráfico, desaparezcan las marcas de 0,.2, 0.4, 0.6 y 0.8 y aparezcan en 0.25, 0.50 y 0.75. He probado varias cosas que he visto por Googe pero no me han funcionado. ¿Alguna idea? library(ltm) # creo el modelo modelo <- ltm(LSAT ~ z1) # represento el modelo plot(modelo, legend = TRUE, cx = "bottomright", lwd = 3,cex.main = 1.5, cex.lab = 1.3, cex = 1.1,main="") # creamos las líneas horizontales abline(h=0.25, col="purple") abline(h=0.50, col="red") abline(h=0.75, col="green&quot...

...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 develop even though it originally came from another package? Or, is it more appropriate for my package to depend on the package where the data originally live? The functions planned for the current distrib...

...and variables maps. I will appreciate any help that expand these reproducible scripts. #How to conduct polychoric principal component analysis pPCA using #either of these packages library(psych) library(FactoMineR) library(nsprcomp) #Bock and Liberman (1970) data set of 1000 observations of the LSAT #from psych data(bock) responses <- table2df(bock.table[,2:6],count=bock.table[,7], ??????????????? labs= paste ("lsat6.",1:5,sep="")) fix(responses) describe(responses) #Estimate the polychoric correlation matrix to be used in #PCA using psych W <- polychoric(response...

...ogram written in c# > running under mono. > > I already know the Windows API LookupSID ( > https://docs.microsoft.com/en-us/windows/win32/api/winbase/nf-winbase-lookupaccountsida) > and its underlying raw RPC call ( > https://docs.microsoft.com/en-us/openspecs/windows_protocols/ms-lsat/eb7ac899-e697-4883-93de-1e60c7720c02 > ). > > I've also already implemented the raw RPC call on Windows in C# to be able > to test null session > (https://github.com/vletoux/pingcastle/blob/master/RPC/lsa.cs) > So i understand what I'm doing. > > I want to port my c#...