[R] NMDS with missing data?
David Carlson
dcarlson at tamu.edu
Thu May 9 15:50:54 CEST 2013
Since you pass your entire data.frame to metaMDS(), your first error
probably comes from the fact that you have included ID as one of the
variables. You should look at the results of
str(dat)
You can drop cases with missing values using
> dat2 <- na.omit(dat)
> metaMDS(dat2[,-1])
would run the analysis on all but the first column (ID) with all the cases
containing complete data. But that assumes that sex and exposure are not
factors.
Or you could use one of the distance functions in dist() which adjust for
missing values. However dist() does not have an option to use Bray-Curtis
(the default in metaMDS()). Bray-Curtis is designed for comparing species
counts or proportions so it is not clear that it is an appropriate
dissimilarity measure for your data. Further, your data seem contain a
mixture of measurement scales and/or magnitudes so some variable
standardization or transformations are probably necessary before you can get
any useful results from MDS.
-------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of Elizabeth Beck
Sent: Wednesday, May 8, 2013 3:39 PM
To: r-help at r-project.org
Subject: [R] NMDS with missing data?
Hi,
I'm trying to run NMDS (non-metric multidimensional scaling) with R vegan
(metaMDS) but I have a few NAs in my data set. I've tried to run it 2 ways.
The first way with my entire data set which includes variables such as ID,
sex, exposure, treatment, sodium, potassium, chloride....
mydata.mds<-metaMDS(dat)
I get the following error:
in if (any(autotransform, noshare > 0, wascores) && any(comm < 0)) { :
missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In Ops.factor(left, right) : < not meaningful for factors
2: In Ops.factor(left, right) : < not meaningful for factors
3: In Ops.factor(left, right) : < not meaningful for factors
4: In Ops.factor(left, right) : < not meaningful for factors
5: In Ops.factor(left, right) : < not meaningful for factors
The second way with only those last biochemical variables (29 in total).
mydata.mds<-metaMDS(measurements)
I get this error:
Error in if (any(autotransform, noshare > 0, wascores) && any(comm < 0)) {
:
missing value where TRUE/FALSE needed
My go to "na.rm=TRUE" does nothing. Any ideas on how to account for NAs and
if so which of the above options I should be using?
Thanks!
Elizabeth
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