[R-sig-ME] gls for generalized linear model

[ONKELINX, Thierry]

What is the rationale for testing the significance of just a random intercept? If you think a random intercept is needed because of the design of your experiment, then it should be in the model. Regardless the variance of the random intercept or its significance.

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 op inbo.be
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 op r-project.org [mailto:r-sig-mixed-models-bounces op r-project.org] Namens ChenChun
Verzonden: maandag 16 september 2013 12:48
Aan: r-sig-mixed-models op r-project.org
Onderwerp: [R-sig-ME] gls for generalized linear model

Dear R users,
I am fitting a GLMM model on survival:
fit1 <- lmer(alive ~ treatment + (1 | expID), family = binomial, data = Data, REML = TRUE) I would like to test whether the random effect is significant. Normally for a linear model, I could test it against a model without random effect using gls, for instancegld(response ~ variable, data=..., method="REML"). However, it seems that gls does not support the generalized linear model (family = binomial). May I ask how I can test the random effect in this case?
Thanks
Regards,
tiantian
        [[alternative HTML version deleted]]

_______________________________________________
R-sig-mixed-models op 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.