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Hello!   I would like to sample 30 % of cases (with at least 1 value lower than 3) and among them I want to set all values lower than 3 (within selected cases) as NA (NMAR- Not missing at random). I managed to sample cases, but I don’t know how to set values (lower than 3) as NA.   R code:   x <-

Dear all, I would like to generate 500 matrices of 20 numbers from standard normal distribution with names x1,x2,x3,….x500.   I tried with loop for, but I don’t know how to name matices : for (i in 1:500)  {    x[[i]] <- matrix(rnorm(20), 4)     } Any suggestion? Thanks,  Blaž [[alternative HTML version deleted]]

Dear R buddies, I’m trying to run Principal Component Analysis, package princomp: http://stat.ethz.ch/R-manual/R-patched/library/stats/html/princomp.html. My question is: why do I get different results with pca = princomp (x, cor = TRUE) and pca = princomp (x, cor = FALSE) even when I standardize variables in my matrix? Best regards, Blaž Simčič [[alternative HTML version deleted]]

Hello! I would like to sample 5 % of cases and from 1 to 3 variables within selected cases and set them as NA (MCAR-Missing completely at random). I managed to sample cases and variables, but I don’t know how to set them as NA. R code: N <- 1000      ####number of cases n <- 12           ####number of variables X <- matrix(rnorm(N * n), N, n)    ####matrix pMiss <- 0.05