[R] Percentage cover data with many zeros

peter dalgaard pdalgd at gmail.com
Sat Jan 24 17:37:54 CET 2015

Don't worry, there are plenty of halfwits around here. However, this is about stats theory,  and not really about R, so you're better off trying CrossValidated, aka stats.stackexchange.com


> On 24 Jan 2015, at 14:26 , Ben Brooker <awe.ben at googlemail.com> wrote:
> Hi,
> I am new to R and have not had the most exposure to statistics.
> I have a dataset of percentage cover (so 0-100) for certain species in 3
> different shore zones (High, mid and low). The data was recorded for
> different protected areas as well (17 of them) and my number of obs is
> large (3358). I'm obviously interested in the difference in percentage
> cover of species between shore zones as well as between protected areas.
> The problem is that my data contains loads of zeros and I haven't dealt yet
> in statistics with how to manipulate the data so as to perform robust tests
> on it. I previously used Kruskal-Wallis ANOVAs to look at cover differences
> in shore zone but I am worried that it is inappropriate because of the
> large sample size that I have and because my variances are not equal.
> I've read a bit about using a zero-inflated negative binomial regression to
> fit to my data, but I'm not sure if that will work because it is for count
> data.
> I would very much appreciate it if someone could point me in the correct
> direction wrt a transformation that may help or an appropriate model to fit
> or test to use. I've searched quite a bit but I'm a out of my depth.
> PS sorry if I sound like a halfwit
> Thanks a lot
> Ben
> 	[[alternative HTML version deleted]]
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Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com

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