Mixed model on few individuals
Dear Simon, Interesting problem. 3 individuals is too small for a random effect of individual see http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#should-i-treat-factor-xxx-as-fixed-or-random However you still have 51 trials. So that would be relevant to include as a random effect. The azimuth and elevation are your response variables? In that case you rather have temporal autocorrelation. The nlme package has several models for temporal autocorrelation among the residuals. The INLA package provides models where the random effects have temporal autocorrelation. Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance thierry.onkelinx at inbo.be Havenlaan 88 bus 73, 1000 Brussel 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 /////////////////////////////////////////////////////////////////////////////////////////// <https://www.inbo.be> 2018-02-26 9:28 GMT+01:00 Simon POTIER <sim.potier at gmail.com>:
Dear all,
First, I will try to be the most comprehensible, if not, do not hesitate to
ask for more information.
I am working on a project with collaborators, and I am trying to analyse
the data. For one question, however, I do not feel confident with my
method, but I do not know how I can analyse the data in a different way.
We are working on visual fixation of a prey while hunting, with a new
method of high accuracy. This method is very interesting but implies that
we cannot use many individuals (because of different things that are not of
interest here I think).
My major problem here is that I have "only" 3 individuals and 51 trials
(almost equilibrate per individual).
I also have 3 different conditions (i.e. 3 types of prey). All these
conditions have been repeated for the 3 individuals.
In total, the dataset is relatively large as I have more than 6000 points
(large for behavioural study), but, as I wrote, with only 3 individuals.
Regarding this type of dataset, I am wondering whether I can use mixed
model to compare the visual fixation according to the different conditions.
So here are my two questions :
1) Can I use mixed models with only 3 individuals? If not, do you know if I
can use another model? Or should I compare each individual independently?
2) My data are spatio-temporal (visual fixation in times: One Azimuth and
one elevation every X sec). How can I implement this autocorrelation in my
model?
I am sincerely grateful if someone can be of any help. Sorry If similar
question has been posted before, I did not find it.
Best regards,
Simon Potier
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