[R-sig-ME] Mixed Model Specification

[ONKELINX, Thierry]

Dear Tom,

Your dataset is very small. Consider yourself lucky when a simple glm gives reasonable estimates. A rule of thumb is that your need 10 effective observations per parameter. The number of effective observations in the binomial case is equal to the number of presences or absences (the smallest of the two). If you are very lucky: 25/2 = 12. So at best you can fit a model with 1 (one) parameter. e.g. glm(Presence ~ Substrate) when Substrate has only 2 (two) levels.

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
+ 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

________________________________________
Van: r-sig-mixed-models-bounces op r-project.org [r-sig-mixed-models-bounces op r-project.org] namens Worthington, Thomas A [thomas.worthington op okstate.edu]
Verzonden: donderdag 26 juni 2014 23:00
Aan: r-sig-mixed-models op r-project.org
Onderwerp: [R-sig-ME] Mixed Model Specification

Dear All

I have a question about the use of a mixed effects model. I have presence/absence data for a mussel species collected at 25 sites. I wish to relate the presence/absence to a number of environmental variables and also want to take into account site. Is it feasible to use site as a random effect as I have only one replicate per site   e.g.

M1<-glmer(Presence ~ Substrate, (1 | Site), family = binomial, data = data)

Best wishes

Tom

_______________________________________________
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.