R help - Nov 2009 - How shall one present LRT test statistic in a scientific journal ?

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.
-- 
View this message in context:
http://old.nabble.com/How-shall-one-present-LRT-test-statistic-in-a-scientific-journal---tp26532480p26532480.html
Sent from the R help mailing list archive at Nabble.com.

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

-- 
David Winsemius, just a guy who formerly argued about such matters.


>
> Thank you very much,
> Julien.
> -- 
> View this message in context:
http://old.nabble.com/How-shall-one-present-LRT-test-statistic-in-a-scientific-journal---tp26532480p26532480.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT