What do you get with str(mortdata)? The error message indicates that at least one of the variables is not numeric and the second suggests it is a factor. You said the values were coded binomially, but they must be numeric, e.g. 0, 1 and not "Present" "Absent" or something like that. If they are all factors, something like
mortdata1 <- sapply(mortdata, as.numeric)-1 would convert factor levels of 1 and 2 to 0 and 1. ------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Kirsten Green Sent: Tuesday, October 18, 2016 12:28 PM To: r-help@r-project.org Subject: [R] MDS, line of best fit, and id of variables Hi, I have created a dataset that includes 28 rows (burials) and 27 columns (variables) that are coded binomially. I have gotten metaMDS to run in the pst but now can't seem to get it run at all. Error message: > mortdata.mds <- metaMDS(mortdata) Error in FUN(X[[i]], ...) : only defined on a data frame with all numeric variables In addition: Warning message: In Ops.factor(left, right) : ‘<’ not meaningful for factors I'd like to create a 3D MDS plot and add the line of best fit for the 3 dimensions (3 variables). I am also trying to figure out, or understand, which variables are causing the variation. I ran PCA and it told me that with 3 variables approximately 50% of the data variation is explained. So I assumed that meant that running MDS in 3 dimensions would show me 3 variables causing the variation but I can't get that to work. Here is my code so far (i've also attached it to the email): mortdata<-read.csv("Table5.5.csv", header=TRUE) mortdata row.names(mortdata) <- mortdata[,1] mortdata <- mortdata[,-1] mortdata mortdata.mds <- metaMDS(mortdata) mortdata.mds.alt <- metaMDS(mortdata, distance="euclidean", k=3, trymax=50, autotransform=FALSE, noshare=FALSE) *object = mortdata.mds.alt names(mortdata.mds.alt) mortdata.mds.alt summary(mortdata.mds.alt) *stress plot stressplot(mortdata.mds.alt) x <- mortdata.mds.alt$species y <- mortdata.mds.alt$points na.exclude(mortdata.mds.alt) vScoresScale <- scale(, center = TRUE, scale = TRUE) plot(mortdata.mds.alt) plot(mortdata.mds.alt, type="t") *multiple linear regression model lm(formula = x ~ y) abline(lm(x ~ y), col="red") *scatterplot3D library(scatterplot3d) attach(mortdata.mds.alt) scatterplot3d(mortdata.mds.alt, x="sampleScores", y="variableScores", main="3D Scatterplot") Any help would be greatly appreciated. I can also send the dataset if that helps. -- *Kirsten Green* kagbo...@gmail.com 916-712-5193 ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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 -- To UNSUBSCRIBE and more, see 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.
