See ?log1p
Best,
Philippe Grosjean
..°}))
) ) ) ) )
( ( ( ( (Prof. Philippe Grosjean
) ) ) ) )
( ( ( ( (Numerical Ecology of Aquatic Systems
) ) ) ) ) Mons-Hainaut University, Belgium
( ( ( ( (
Dear Nate,
Much depend on the nature of your data. If they are counts, then I would
recommend to use glm(count ~x + y + z, family = poisson) instead of
lm(log(count) ~ x + y + z). Otherwise people tend to use a log(x+1)
transformation.
HTH,
Thierry
Dear Philippe,
while I don't like to quibble about rules-of-thumb (since they are, as
you rightly point out, without foundation in statistical theory), I
would like to correct the impression that you gave in your email.
Let's take an hypothetical example along the lines you proposed (or at
I am a new user to R and I would like to ask for your help.
I calculated CCA with vegan and ade4 too. I imported my
datas in the same form to packages but the graphics show
others. The arrows are in different direction with different
angel in the both diagrams. Why is it like that?
Where can I
Many thanks to Carsten, Philippe, and Nate for a very informative and
entertaining discussion of something I have always wondered about,
having heard suggestions for both approaches. At least now I have a
better understanding of the rationale for each!
Matt
Thanks very much indeed Carsten and Philippe!
Lots to consider. I should have specified this before, but the
variable with zero values that I would like to log (ln) transform does
consist of many small values. The range is between 0.00 and 0.35,
since this variable is the percentage
Hi Nate,
Here is my 2 cents worth after coming in late to this discussion.
The fact that your data are proportions is important as it suggests how
the data may vary. Do you have the numerator and denominator used to
calculate the proportions? If so then I would suggest that you should be
Hey there Ben,
I was just checking out your book actually. When you say that I should do this
as a binomial
analysis, is that because this variable is distributed similarly to a
zero-inflated binomial
distribution?
Since all my data are non-normal, and my comparisons have heterogeneous
