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/

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