search for: congeneric

Hi, I'm trying to convert Matrix into a list format and have written the following code: path = ("C:/2PL_Alpha_C_2PL_Loading") setwd(path) getwd() congeneric = matrix(rep(NA,36),nrow=6,ncol=6) conFirst = matrix(rep(NA,36),nrow=6,ncol=6) conFirstTwenty = rep(NA, 20) k = 1 #Reading all the Alpha and Congeneric 2PL values into variables alpha <- read.table("2PLAlphaGenPars_1.dat", header=FALSE) congeneric <- read.table("C_parameter_e...

...Parallel Latent CTT model and this is what i have done so far: (START) #Importing psych library for all the simulation related functions library(psych) # Settting the working directory path to C:/NCME path="C:/NCME" setwd(path) #Using the function to generate the data GenData <- congeneric.sim(N=500, loads = c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1), short = FALSE) #Rounding upto 2 decimal places while showing the correlation matrix round(cor(GenData$observed),2) #Factor Score FactorScore=factor.pa(GenData$observed,1,scores = "TRUE", rotate="none") round(cor(F...

...l=n.items) Observed_Scores = matrix(rep(NA,n.exams*n.items),nrow=n.exams,ncol=n.items) #filling item parameters into beta.values beta.values = runif(n.items,-2,2) #Calculating Threshold thresh.values = .5 * beta.values #for (i in 1:10) #{ #Using the function to generate the data GenData <- congeneric.sim(N=500, loads = rep(.5,20), err=NULL, short = FALSE) Observed_Scores = GenData[1] Regards Nidhi Kohli

...ems) str(Observed_Scores) for (k in 1:10) { #Setting the starting point for seed set.seed(k) #filling item parameters into beta.values beta.values = runif(n.items,-2,2) #Calculating Threshold thresh.values = .5 * beta.values #Using the function to generate the Parallel Model CTT data GenData <- congeneric.sim(N=500, loads = rep(.5,20), err=NULL, short = FALSE) #Storing Observed Score in a variable Observed_Scores = GenData[[3]] #Exporting Observed scores to output file ObservedScores_Data <- paste("Observed_Scores_",k,".dat") write.table(Observed_Scores,ObservedScores_Data,ro...

Hello all, I'm trying to create covariance matrices that, when processed via CFA methods (in the sem package) will produce exact fit with simple structure down to poor fit with cross loadings. What is the best way to do this? I don't really need to have the exact loop code, but maybe an explanation of how to make a few of the matrices or an explanation of the rationale behind performing

...ems) str(Observed_Scores) for (k in 1:10) { #Setting the starting point for seed set.seed(k) #filling item parameters into beta.values beta.values = runif(n.items,-2,2) #Calculating Threshold thresh.values = .5 * beta.values #Using the function to generate the Parallel Model CTT data GenData <- congeneric.sim(N=500, loads = rep(.5,20), err=NULL, short = FALSE) #Storing Observed Score in a variable Observed_Scores = GenData[[3]] #Exporting Observed scores to output file ObservedScores_Data <- paste("Observed_Scores_",k,".dat") write.table(Observed_Scores,ObservedScores_Data,ro...

...=n.exams,ncol=n.items) > > > #filling item parameters into beta.values > beta.values = runif(n.items,-2,2) > > #Calculating Threshold > thresh.values = .5 * beta.values > > > #for (i in 1:10) > #{ > > #Using the function to generate the data > GenData <- congeneric.sim(N=500, loads = rep(.5,20), err=NULL, short = > FALSE) > Observed_Scores = GenData[1] > > Regards > Nidhi Kohli > > > > ------------------------------ > > Message: 8 > Date: Sat, 10 Jan 2009 17:16:15 +0100 > From: "Borja Soto Varela" <borja.sot...

Hi All, I've been having a little trouble with creating a loop that will run a a series of t.tests for inspection, Below is the code i've tried, and some checks i've looked at. I've used the get(paste()) idea as i was told previously that the use of the eval should try and be avoided. I've run a single syntax to check that my systax is correct and works without any problems