[R] CoDA: Count Zeros in Biological Data
gunter.berton at gene.com
Fri Jun 20 04:37:09 CEST 2014
1. This is a question about statistical methodology, not R. Hence
2. Replies should therefore be private.
3. Consult the literature.
Genentech Nonclinical Biostatistics
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
On Thu, Jun 19, 2014 at 6:23 PM, Rich Shepard <rshepard at appl-ecosys.com> wrote:
> I have several small biological count-based data sets with one or more
> rows having zero proportion. The other proportions in the row sum to 1.000
> (or 0.9999 in the sixth data row below because of rounding errors in the
> computer). An example is:
> sampdate filter gather graze predate shred
> 2000-07-18 0.0550 0.5596 0.0734 0.2294 0.0826
> 2003-07-08 0.0734 0.6147 0.0183 0.2294 0.0642
> 2005-07-13 0.1161 0.5714 0.0357 0.1696 0.1071
> 2006-06-28 0.1000 0.4667 0.1500 0.1333 0.1500
> 2010-09-14 0.0778 0.6111 0.0444 0.1889 0.0778
> 2011-07-13 0.0879 0.5714 0.0659 0.2747 0.0000
> 2012-07-11 0.1042 0.5313 0.0625 0.2396 0.0625
> My concern is that in most field-biological (ecological/environmental)
> data there can be two explanations for zero counts: the organism was not
> present on that date or it was present but not collected. There is no way to
> determine which case holds true in each instance, but the ecological
> interpretations differ.
> The zCompositions package offers several methods of imputing a value to
> replace the zeros. As I'm completely new to compositional data analyses
> (CoDA) I would appreciate advice on how to select the most appropriate
> method for these data sets. The available methods are: Geometric Bayesian
> multiplicative, BM, (GBM, default); square root BM (SQ); Bayes-Laplace BM
> (BL); count zero multiplicative (CZM); user-specified hyper-parameters
> These biological data seem to me to be different from geochemical or
> economic data I see in package data sets or the CoDA references I've
> acquired and read.
> Advice and suggestions (including references to application of CoDA to
> ecological/environmental data) will be appreciated.
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> and provide commented, minimal, self-contained, reproducible code.
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