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 ?
Thank you very much,
Julien.
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