On Jan 24, 2015, at 8:37 AM, peter dalgaard wrote:

> 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

This is useful and correct advice, but if you want to see an excellent 
description of some of the R tools for dealing with zero-inflation, the 
Zeileis, Kleiber & Jackman article on the matter: 
http://www.jstatsoft.org/v27/i08/paper ,  was very helpful in advancing my 
understanding of the subject area.

> 
> -pd
> 
>> On 24 Jan 2015, at 14:26 , Ben Brooker <awe....@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

I wonder if the terms Kruskal-Wallis and ANOVA should be adjacent. I do not 
remember that variances are part of the inference with KW-tests. You might ask 
that in your question to the very helpful group on CrossValidated.com


-- 
David.

>> 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
>> 

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