you can do the following: mat <- cbind(x = runif(15, 50, 70), y = rnorm(15, 2)) mat[sample(15, 2), "x"] <- NA
na.x <- is.na(mat[, 1]) mat[na.x, ] mat[!na.x, ] I hope it helps. Best, Dimitris On 10/15/2010 2:45 PM, Jumlong Vongprasert wrote:
Dear all I have data like this: x y [1,] 59.74889 3.1317081 [2,] 38.77629 1.7102589 [3,] NA 2.2312962 [4,] 32.35268 1.3889621 [5,] 74.01394 1.5361227 [6,] 34.82584 1.1665412 [7,] 42.72262 2.7870875 [8,] 70.54999 3.3917257 [9,] 59.37573 2.6763249 [10,] 68.87422 1.9697770 [11,] 19.00898 2.0584415 [12,] 60.27915 2.5365194 [13,] 50.76850 2.3943836 [14,] NA 2.2862790 [15,] 39.01229 1.7924957 and I want to spit data into two set of data, data set of nonmising and data set of missing. How I can do this. Many Thanks. Jumlong
-- Dimitris Rizopoulos Assistant Professor Department of Biostatistics Erasmus University Medical Center Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands Tel: +31/(0)10/7043478 Fax: +31/(0)10/7043014 Web: http://www.erasmusmc.nl/biostatistiek/ ______________________________________________ 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.