Something like this? > split(FS1, hcli8) $`1` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 1 1 1 0 1 0 0 1 1 0 1 1 1 3 1 0 1 0 0 1 1 0 0 1 0 1 4 1 1 0 0 0 0 1 1 1 1 1 1 7 0 1 0 1 0 0 1 1 0 1 0 1 9 1 1 1 1 0 1 1 0 1 1 1 0 12 1 0 0 0 0 1 1 1 1 1 0 1 13 0 1 1 1 1 0 0 0 1 1 0 1 15 1 0 1 1 0 0 1 0 0 1 0 1 16 1 0 1 0 0 1 1 0 1 0 1 1 19 0 1 0 0 0 0 1 0 0 1 0 1 20 0 1 1 1 0 0 0 1 1 0 0 1 24 1 1 0 1 0 0 1 0 1 1 1 0 26 1 1 1 1 1 1 0 1 0 1 0 1 28 1 0 1 0 1 0 1 1 0 1 1 1 33 1 1 0 1 0 0 0 0 1 1 0 0 38 1 1 1 0 0 0 0 0 1 1 0 0 40 1 0 1 0 0 0 1 0 0 1 1 1 41 1 1 0 0 0 0 0 0 1 1 1 1 43 0 0 1 0 0 0 1 0 1 1 0 1 52 1 1 1 1 0 0 0 1 1 1 0 1 53 1 1 0 0 1 0 0 1 1 1 0 1 56 1 0 1 0 0 1 1 0 1 0 0 0 60 1 1 1 0 1 1 0 1 1 1 0 1
$`2` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 2 0 1 1 1 1 1 1 0 0 1 1 0 5 0 1 0 1 1 1 0 0 0 1 1 1 6 0 0 0 0 1 0 1 0 0 1 1 1 10 1 1 1 1 1 0 1 1 0 1 0 0 11 0 1 0 1 1 0 1 0 1 1 1 1 14 0 0 1 1 1 1 1 1 0 1 1 1 17 0 1 0 0 1 0 0 0 0 0 1 1 18 1 0 0 1 1 1 1 1 0 0 1 1 29 1 1 0 1 0 1 1 1 0 0 1 1 37 1 0 0 1 1 0 1 1 0 1 0 0 42 1 1 0 1 1 1 1 0 0 0 0 0 46 1 1 0 1 0 1 1 0 0 1 0 1 48 0 1 0 0 1 0 1 0 0 1 1 0 50 0 1 0 1 1 1 1 1 0 0 1 0 51 0 0 0 1 1 1 1 0 0 0 1 1 54 0 0 0 1 1 1 1 0 0 1 1 0 58 0 1 0 1 1 1 1 1 1 1 1 0 61 1 0 1 0 1 1 1 1 0 1 0 0 $`3` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 8 0 1 1 0 0 1 0 1 1 1 1 0 21 0 1 0 0 1 1 0 1 0 1 1 0 22 1 1 0 0 0 1 1 1 0 0 1 0 25 0 1 0 0 0 1 0 1 0 1 1 0 27 1 1 0 0 1 1 0 1 1 0 0 0 32 1 1 1 0 1 1 0 1 0 0 1 0 36 1 1 0 0 0 1 0 1 0 0 0 0 44 1 1 1 1 1 1 0 1 0 0 0 0 63 0 1 1 0 1 1 0 0 1 1 1 0 $`4` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 23 0 0 1 1 0 0 0 0 0 1 0 0 34 0 1 1 1 0 0 0 1 0 1 0 0 $`5` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 30 0 0 0 0 1 1 0 0 1 1 0 1 31 0 1 1 0 1 0 0 0 1 0 1 1 35 0 0 1 0 1 1 0 0 1 1 0 1 47 0 0 1 0 1 0 0 0 1 0 0 1 49 1 0 0 0 1 1 0 0 1 1 1 0 55 1 0 1 0 1 0 0 0 0 1 1 0 59 0 0 1 0 1 0 0 0 1 0 1 1 $`6` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 39 0 0 0 0 1 0 1 1 0 0 0 0 62 0 0 0 0 1 0 1 1 0 0 0 1 $`7` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 45 1 1 0 0 0 0 0 0 0 0 1 0 $`8` X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 57 0 0 1 0 0 1 0 1 0 0 1 1 ------- David > -----Original Message----- > From: Bob Green [mailto:bgr...@dyson.brisnet.org.au] > Sent: Sunday, November 18, 2012 3:22 PM > To: dcarl...@tamu.edu; r-help@r-project.org > Subject: RE: [R] Examining how cases are similar by cluster, in cluster > analysis > > David, > > > Many thanks, I'm sure this will be helpful. What would also be > helpful is if I can extract each cluster and examine id by variable, > within the respective cluster. I could index the variables for each > cluster and run such an analysis but thre must be a more efficient > way of doing this (especially as I experiment with different > clustering methods) > > Thanks again, > > Bob > > At 06:44 AM 19/11/2012, David L Carlson wrote: > >If you just want a summary of the mean for each variable in each > >cluster, this will get you there: > > > > > set.seed=42 > > > FS1 <- data.frame(matrix(sample(c(0, 1), 12*63, replace=TRUE), > >nrow=63, > >+ ncol=12)) > > > dmat <- dist(FS1, method="binary") > > > cl.test <- hclust(dmat, method="average") > > > plot(cl.test, hang=-1) > > > hcli8 <- cutree(cl.test, k=8) > > > tbl <- aggregate(FS1, by=list(Group=hcli8), mean) > > > print(tbl, digits=4) > > Group X1 X2 X3 X4 X5 X6 X7 X8 > >X9 > >1 1 0.5122 0.6829 0.6829 0.6341 0.5854 0.5854 0.6829 0.6341 > >0.5366 > >2 2 0.0000 0.0000 0.0000 1.0000 0.6667 0.6667 0.0000 0.6667 > >0.0000 > >3 3 0.9286 0.1429 0.1429 0.1429 0.2857 0.5714 0.7857 0.3571 > >0.8571 > >4 4 1.0000 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 > >0.0000 > >5 5 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 > >1.0000 > >6 6 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 1.0000 > >0.0000 > >7 7 1.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 > >0.0000 > >8 8 0.0000 1.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 > >0.0000 > > X10 X11 X12 > >1 0.4146 0.4634 0.561 > >2 0.6667 0.0000 0.000 > >3 0.8571 0.6429 0.500 > >4 1.0000 0.0000 0.000 > >5 0.0000 1.0000 0.000 > >6 0.0000 0.0000 1.000 > >7 0.0000 0.0000 0.000 > >8 0.0000 0.0000 0.000 > > > > >---------------------------------------------- > >David L Carlson > >Associate Professor of Anthropology > >Texas A&M University > >College Station, TX 77843-4352 > > > > > -----Original Message----- > > > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > > > project.org] On Behalf Of Bob Green > > > Sent: Sunday, November 18, 2012 5:00 AM > > > To: r-help@r-project.org > > > Subject: [R] Examining how cases are similar by cluster, in > > > cluster analysis > > > > > > Hello, > > > > > > I used the following code to perform a cluster analysis on a > > > dataframe consisting of 12 variables (coded as 1,0) and 63 > > > cases. > > > > > > > > > > > > FS1 <- read.csv("D://Arsontest2.csv",header=T,row.names=1) > > > > > > str(FS1) > > > > > > dmat <- dist(FS1, method="binary") > > > > > > cl.test <- hclust (dist(FS1, method ="binary"), "ave") > > > > > > plot(cl.test, hang = -1) > > > > > > > > > > > > Each case has an id and the dendogram identifies the respective > > > cases > > > which constitute each cluster. What I am seeking advice on is > > > how to > > > examine the variables on which the cases are similar, within > > > each cluster. > > > > > > > > > > > > sort (hcli8 <- cutree(cl.test, k=8)) identifies that the > > > following > > > cluster 2is comprised of the following cases: > > > > > > 1641 2295 2594 2654 2799 3213 3510 3513 2958 3294 > > > > > > 2 2 2 2 2 2 2 > > > 2 > > > 2 2 > > > > > > > > > > > > This code provides means for the variables by cluster. In > > > relation to > > > cluster 2 it appears the cases should have no clear motive and > > > be depressed : > > > > > > round(sapply(x, function(i) colMeans(FS1[i,])),2) > > > > > > [,1] [,2] [,3] [ ,4] [,5] > > > [,6] [,7] [,8] > > > > > > depressed 0.00 0.33 0.00 0.0 0 0.6 0.00 0.08 > > > > > > unclear 0.33 1.00 1.00 1.0 0 0.0 0.07 0.12 > > > > > > > > > > > > I can manually, examine this variable by variable and look at > > > how > > > each of the cases in cluster 2 are similar on the variables. I > > > am > > > looking at a more efficient and quicker way to do this. > > > > > > Bob > > > > > > ______________________________________________ > > > 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. ______________________________________________ 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.
