How shall one present LRT test statistic in a scientific journal ?

On Nov 26, 2009, at 12:14 PM, JVezilier wrote:

Hello !!

I'm recently having a debate with my PhD supervisor regarding how to
write
the result of a likelihood ratio test in an article I'm about to submit.

I analysed my data using "lme" mixed modelling.

To get some p-values for my fixed effect I used model simplification
and the
typical output R gives looks like this:

model2 = update ( model1,~.-factor A)
anova (model1, model2)

      Model df       AIC             BIC         logLik         Test
L.Ratio     p-value
model 1     1 26  -78.73898   15.29707     65.36949
model 2     2 20  -73.70539   -1.36997     56.85270   1 vs 2    17.03359
0.0092

I thought about presenting it very simply copying/pasting R table and
writing it like: "factor A had a significant effect on the response
variable
(Likelihood ratio test, L-ratio = 17.033, p = 0.0092)"

But my boss argued that it's too unusual (at least in our field of
evolutionary biology) and that I should present instead the LR statistic
together with the corresponding Chi^2 statistic since the likelihood
ratio
is almost distributed like a Chi2 (df1-df2), and then write down the
p-value
corresponding to this value of Chi.

I looked up in the current litterature but cannot really find a proper
answer to that dilmena.

So, dear evolutionary biologists R users, how would you present it ?

I am not an evolutionary biologist, but presumably your supervisor is
one. Why are you picking a fight not only with him but with your
prospective audience when there is no meaningful difference? Here is the
p-value you would get with his method:

1-pchisq( 2*(65.36949 -  56.85270), df=6)

[1] 0.009160622