Not really. I would recommend to read the first point under that entry: perhaps you shouldn't test the significance of a random effect.

If you think a random effect is required due to the design, then include it.

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx@inbo.be<mailto:Thierry.Onkelinx@inbo.be>
www.inbo.be<http://www.inbo.be/>

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

Van: Alan Haynes [mailto:aghaynes@gmail.com]
Verzonden: dinsdag 13 november 2012 7:58
Aan: Ellen Pape
CC: ONKELINX, Thierry; r-sig-mixed-models@r-project.org
Onderwerp: Re: [R-sig-ME] relative importance of independendent variables in lm and lme models

I think what Thierry was probably getting at was that you should compare the lme with a gls model rather than an lm model. I believe gls and lm are similar, although they make subtly different assumptions about the data, perhaps even none when no corStruct etc are used. Mixed Effects

For the importance of independent variables question you might want to look at the section of the FAQ related to R2 values perhaps. Or the importance function in the AICcmodavg package.

HTH

Alan

--------------------------------------------------
Email: aghaynes@gmail.com<mailto:aghaynes@gmail.com>
Mobile: +41794385586
Skype: aghaynes

On 12 November 2012 13:00, Ellen Pape <Ellen.Pape@ugent.be<mailto:Ellen.Pape@ugent.be>> wrote:
Dear Thierry

So, just to make sure I understand what you're saying:

Are you saying I shouldn't compare lme models with lm models using anova
(which carries out a likelihood ratio test)? It is stated like this on
the website you're referring to, but in the book of Pinheiro and Bates
it is done (on page 155).

So, according to this website I should compare lme with random factor
with lm without random factor with the package RLRsim? But what exactly
is the difference between a restricted and a (unrestricted) likelihood
ratio test?

And the answer to my question, how to determine the importance of
independent variables in a lme model (preferably in a way that the same
method can be applied to regular lm models)?

Thanks!!

*/Ellen Pape (PhD student)/*

Ghent University
Marine Biology Research Group
Krijgslaan 281, S8
9000 Ghent (Belgium)

Email: Ellen.Pape@Ugent.be<mailto:Ellen.Pape@Ugent.be> <mailto:Ellen.Pape@Ugent.be<mailto:Ellen.Pape@Ugent.be>>
Tel: ++ 32 (0)9 264 85 23<tel:%2B%2B%2032%20%280%299%20264%2085%2023>
Fax: ++ 32 (0)9 264 85 98<tel:%2B%2B%2032%20%280%299%20264%2085%2098>
On 12/11/2012 11:47, ONKELINX, Thierry wrote:
> Dear Ellen,
>
> Have a look at http://glmm.wikidot.com/faq and search for 'How can I test whether a random effect is significant?'
>
> Best regards,
>
> Thierry
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
> + 32 2 525 02 51<tel:%2B%2032%202%20525%2002%2051>
> + 32 54 43 61 85<tel:%2B%2032%2054%2043%2061%2085>
> Thierry.Onkelinx@inbo.be<mailto:Thierry.Onkelinx@inbo.be>
> www.inbo.be<http://www.inbo.be>
>
> To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces@r-project.org<mailto:r-sig-mixed-models-bounces@r-project.org> [mailto:r-sig-mixed-models-bounces@r-project.org<mailto:r-sig-mixed-models-bounces@r-project.org>] Namens Ellen Pape
> Verzonden: zondag 11 november 2012 16:45
> Aan: r-sig-mixed-models@r-project.org<mailto:r-sig-mixed-models@r-project.org>
> Onderwerp: [R-sig-ME] relative importance of independendent variables in lm and lme models
>
> Dear all,
>
> I apologize if my question is a bit stupid, but I'm fairly new to the field of mixed effect modelling.
>
> I have performed several regressions, during which I also tested for the significance of a random grouping variable. Most of the time, the random factor was not statistically significant but it was for some regressions.
>
> I was wondering how to calculate the relative importance of the independent variables (I guess for the lme model I also need to look at the importance of the random variable?) for both lm and lme models?
>
> Thanks!
> Ellen
> --
> */Ellen Pape (PhD student)/*
>
> Ghent University
> Marine Biology Research Group
> Krijgslaan 281, S8
> 9000 Ghent (Belgium)
>
> Email: Ellen.Pape@Ugent.be<mailto:Ellen.Pape@Ugent.be> <mailto:Ellen.Pape@Ugent.be<mailto:Ellen.Pape@Ugent.be>>
> Tel: ++ 32 (0)9 264 85 23<tel:%2B%2B%2032%20%280%299%20264%2085%2023>
> Fax: ++ 32 (0)9 264 85 98<tel:%2B%2B%2032%20%280%299%20264%2085%2098>
>
>
>          [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models@r-project.org<mailto:R-sig-mixed-models@r-project.org> mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * *
> Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document.
> The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.


        [[alternative HTML version deleted]]

_______________________________________________
R-sig-mixed-models@r-project.org<mailto:R-sig-mixed-models@r-project.org> mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

* * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * *
Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document.
The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.

	[[alternative HTML version deleted]]

