[R] comparing levels of aggregation with negative binomial models

[Ben Raymond]

Dear R community,

I would like to compare the degree of aggregation (or dispersion) of  
bacteria isolated from plant material.  My data are discrete counts  
from leaf washes.  While I do have xy coordinates for each plant, it  
is aggregation in the sense of the concentration of bacteria in high  
density patches that I am interested in.
My attempt to analyze this was to fit negative binomial glms to each  
of my leaf treatments (using MASS) and to compare estimates of theta  
and use the standard errors to calculate confidence limits.   My  
values of theta (se) were 0.387 (0.058) and 0.1035 (0.015) which were  
in the right direction for my hypothesis.  However, some of the stats  
literature suggests that the confidence intervals of theta (or k) are  
not very robust and it would be better to calculate confidence  
intervals for 1/k.  Is there a way I can estimate confidence intervals  
for 1/k in R, or indeed a more elegant way of looking at aggregation?

Many thanks for your time.

yours,


Dr Ben Raymond,
NERC Advanced Research Fellow,
Lecturer in Population Genetics,
School of Biological Sciences,
Royal Holloway University of London,
Egham,
Surrey.
TW20 0EX

tel 0044 1784443547
Ben.Raymond at rhul.ac.uk