Technically the definition of the nat log of zero is actually an asymptote.

What does zero mean in your data? That is the key issue you must approach
before modifying the information.  If zero means "too small to measure but
not likely zero," then you can do some decimal estimation or I think you
can use a tobit model, but I'm not super familiar with those.  X+1 or X+0.1
etc. is typically used with count data.
However, if the data do not mean that, or are actually some form of ratios,
then when y < z, the ln (y/z) will be negative, so when you add one, you
will have a bunch of zeros that cause you to lose data!
I vaguely recall something about right and left censored models or
something.  However, you better make sure, I'm pulling this out of
somewhere smelly because this is something I read once and I don't remember
where.  But, maybe it will give you a place to start?

Malcolm


On Tue, Feb 11, 2014 at 11:56 PM, Jason Hernandez <
[email protected]> wrote:

> Some time ago, I inquired about ways to analyze percent cover data, and
> one of the suggestions was to test for heterogeneity.  The snag, however,
> is that this requires multiplying each cell value by its natural log.  My
> data set has a lot of zero values, which are important to keep; but of
> course there is no natural log of zero.  Is there a way to adjust the
> analysis to included these zero values?  i have not managed to find
> anything on this.
>
> Jason Hernandez
>
>


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