Dear Thanoon, You might look at the various item simulation functions in the psych package.
In particular, for your problem: R1 <- sim.irt(10,1000,a=3,low = -2, high=2) R2 <- sim.irt(10,1000,a=3,low = -2, high=2) R12 <- data.frame(R1$items,R2$items) #this gives you 20 items, grouped with high correlations within the first 10, and the second 10, no correlation between the first and second sets. rho <- tetrachoric(R12)$rho #find the tetrachoric correlation between the items lowerMat(rho) #show the correlations cor.plot(rho,numbers=TRUE) #show a heat map of the correlations Bill On Aug 4, 2014, at 8:08 PM, thanoon younis <thanoon.youni...@gmail.com> wrote: > Dear R-users > i need your help to solve my problem in the code below, i want to simulate > two different samples R1 and R2 and each sample has 10 variables and 1000 > observations so i want to simulate a data with high correlation between > var. in R1 and also in R2 and no correlation between R1 and R2 also i have > a problem with correlation coefficient between tow dichotomous var. the R- > program supports just these types of correlation coefficients such as > pearson, spearman,kendall. > > thanks alot in advance > > Thanoon > > > ords <- seq(0,1) > p <- 10 > N <- 1000 > percent_change <- 0.9 > > R1 <- as.data.frame(replicate(p, sample(ords, N, replace = T))) > R2 <- as.data.frame(replicate(p, sample(ords, N, replace = T))) > # pearson is more appropriate for dichotomous data > cor(R1, R2, method = "pearson") > > > # subset variable to have a stronger correlation > > > v1 <- R1[,1, drop = FALSE] > v1 <- R2[,1, drop = FALSE] > # randomly choose which rows to retain > keep <- sample(as.numeric(rownames(v1)), size = percent_change*nrow(v1)) > change <- as.numeric(rownames(v1)[-keep]) > > # randomly choose new values for changing > new.change <- sample(ords, ((1-percent_change)*N)+1, replace = T) > > # replace values in copy of original column > v1.samp <- v1 > v1.samp[change,] <- new.change > > # closer correlation > cor(v1, v1.samp, method = "pearson") > > # set correlated column as one of your other columns > R1[,2] <- v1.samp > R2[,2] <- v1.samp > R1 > R2 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > William Revelle http://personality-project.org/revelle.html Professor http://personality-project.org Department of Psychology http://www.wcas.northwestern.edu/psych/ Northwestern University http://www.northwestern.edu/ Use R for psychology http://personality-project.org/r It is 5 minutes to midnight http://www.thebulletin.org ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.