[R-sig-ME] GLMM -Firefly Flash
vickmoe7 at gmail.com
Thu Nov 24 12:42:23 CET 2016
Thank you very much. I will try doing it first. You have been vary helpful.
On Wed, Nov 23, 2016 at 6:05 PM, Thierry Onkelinx <thierry.onkelinx at inbo.be>
> Dear Vickly,
> Please keep the mailing list in cc.
> The idea is that you need a sufficient number of observations per
> parameter. 10 to 20 is often used as a rule of thumb. If you have a lower
> number, the model is too complex given the data will probably overfit.
> Think about a simple linear model (intercept + 1 parameter for slope).
> Although you can technically fit this model when you have 2 or 3
> observations, the resulting model is not very useful.
> Best regards,
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> 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
> 2016-11-23 10:37 GMT+01:00 Vickly Mobilim <vickmoe7 at gmail.com>:
>> Hi Thierry,
>> Thank you for the kind reply! That is very helpful.
>> May I know more about the calculation? I have never seen it. How do you
>> use it to know if it is sufficient to build a model?
>> On Nov 23, 2016 5:27 PM, "Thierry Onkelinx" <thierry.onkelinx at inbo.be>
>> Dear Vickly,
>> I assume you have measurements on the individual animals and you can
>> identify the animal during the different exposures. I think you want a
>> model like this: flash_rate ~ treatment * exposure + temperature + humidity
>> + size_ratio + (1|animal_id) This requires -1 + 4 * 3 + 1 + 1 + 1 + 1 = 15
>> parameters. You have 78 * 3 = 234 observations. That is 234 / 15 = 15.6
>> observations per parameter, which reasonable to fit the model.
>> Best regards,
>> 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
>> 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
>> 2016-11-22 18:01 GMT+01:00 Vickly Mobilim <vickmoe7 at gmail.com>:
>>> I've read several writing of yours about GLMM and I thought it would be
>>> best tool to answer my research questions. However, I wasn't sure if I
>>> really need it and my data permit me to use it. That said, I have 78
>>> individuals of firefly divided into four groups (A= 20 indv., B = 20
>>> C = 20 indv. and D = 18 indv.). This is due to several limitations that I
>>> can't take more samples of firefly. I will explain the details of the
>>> experiment below.
>>> I'm hoping that you can advise me on this issue, whether you have seen
>>> cases of low sample size using GLMM or whether GLMM is not suitable for
>>> I expose the fireflies with several intensity of white light according to
>>> their group (Group A = 0.05lux, B = 0.1lux, C = 0.3lux and D = 0.5lux)
>>> measure their flash rates and duration before, during and after exposure
>>> light (repeated measure design). Temperature, humidity and individual
>>> eye-to-body size ratio were also measured. My main aim was to measure the
>>> impact of several light pollution intensity to their flash rates and
>>> duration and taking temperature, humidity and eye-to-body size into
>>> I realized that calculating changes in their flash rates and duration are
>>> achievable by subtracting post-experiment result with pre-experiment
>>> then use unpaired t-test to compare the results. However, my data was not
>>> normal and I used Mann-Whitney U test instead. But this does not take
>>> temperature, humidity and eye-to-body size into account. As I was looking
>>> into the possibility of taking them into account, I found several
>>> technique that is suitable including GLMM but I am not sure if I can
>>> them because according to a statistician I am in consult with, the sample
>>> size is too small to be developed into a model that it would invite more
>>> problem in analysis.
>>> Vickly Mobilim
>>> [[alternative HTML version deleted]]
>>> R-sig-mixed-models at r-project.org mailing list
[[alternative HTML version deleted]]
More information about the R-sig-mixed-models