[R-sig-eco] best choice of GLMM for seed set data
Mehdi Abedi
abedimail at gmail.com
Thu Aug 27 15:33:33 CEST 2015
Thanks Bob for reply.
I have problem that when you have results of effect size i am not sure to
how get only main effect without their levels data. I previously asked this
simple question but i couldn't get clear answer. The question is simple:
how we can have only temp, light and their interactions(similar like output
of anova() without their levels.
*Call:*
glm(formula = cbind(A..hierochuntica, A..hierochunticano) ~ temp *
light, family = binomial)
Deviance Residuals:
Min 1Q Median 3Q Max
-4.4473 -1.1993 0.9904 2.0101 3.6663
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.66616 0.14341 18.591 < 2e-16 ***
temp20/30 0.08538 0.20671 0.413 0.679596
temp25/35 -0.67373 0.18001 -3.743 0.000182 ***
lightlight 0.51189 0.23048 2.221 0.026350 *
temp20/30:lightlight 0.62839 0.37291 1.685 0.091965 .
temp25/35:lightlight 2.09080 0.43729 4.781 1.74e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 334.88 on 47 degrees of freedom
Residual deviance: 209.30 on 42 degrees of freedom
AIC: 331.56
Number of Fisher Scoring iterations: 6
this is by *anova(model,test="Chi")*
Analysis of Deviance Table
Model: binomial, link: logit
Response: cbind(A..hierochuntica, A..hierochunticano)
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev Pr(>Chi)
NULL 47 334.88
temp 2 10.144 45 324.73 0.006271 **
light 1 86.860 44 237.87 < 2.2e-16 ***
temp:light 2 28.569 42 209.30 6.255e-07 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
*anova(model, test="F")*
Analysis of Deviance Table
Model: binomial, link: logit
Response: cbind(A..hierochuntica, A..hierochunticano)
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev F Pr(>F)
NULL 47 334.88
temp 2 10.144 45 324.73 5.0718 0.006271 **
light 1 86.860 44 237.87 86.8597 < 2.2e-16 ***
temp:light 2 28.569 42 209.30 14.2847 6.255e-07 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Warning message:
In anova.glm(model, test = "F") :
using F test with a 'binomial' family is inappropriate
Warm regards,
Mehdi
On Thu, Aug 27, 2015 at 2:38 PM, Bob O'Hara <bohara at senckenberg.de> wrote:
> On 27/08/15 11:57, Mehdi Abedi wrote:
>
>> Dear Thierry,
>> Yes i am using (success, failure) but in this case i need to change all
>> data frame. I was thinking to use codes which is not necessary to create
>> new column when you have a ll of species. Because we know
>> success(germinated seeds) and we know failure (Total seeds -
>> success(germinated seeds)).
>>
>> Yes i used codes with ANOVA but there is no P- value for study.
>>
>> model2<- glmer(cbind(germinated, Nongerminated) ~ temp *light +
>> (1|Replication ), data=growthdata,
>> + family=binomial)
>>
>>> anova(model2)
>>>
>> Analysis of Variance Table
>> Df Sum Sq Mean Sq F value
>> temp 2 30.600 15.300 15.300
>> light 1 46.231 46.231 46.231
>> temp:light 2 22.877 11.439 11.439
>>
> p-values are difficult. See here:
> <http://glmm.wikidot.com/faq>
>
> Better to stick to reporting your effect sizes: your analysis of deviance
> only tells you if you have enough data to see a difference, not how big the
> differences are.
>
> Also, if Replication is 1:nrow(growthdata), you could use a simple GLM and
> estimate your over-dispersion term (the residual deviance divided by the
> residual sum of squares should be OK). You can use this to correct the
> standard errors with summary(glm.obj, dispersion=overdisp).
>
> Bob
>
>
> Warm regards,
>> Mehdi
>>
>>
>> On Thu, Aug 27, 2015 at 1:56 PM, Thierry Onkelinx <
>> thierry.onkelinx at inbo.be>
>> wrote:
>>
>> Dear Mehdi,
>>>
>>> Assuming that you want to model the probability of germination, yes.
>>>
>>> Note that cbind(seed, 100) is WRONG syntax.
>>> CORRECT syntax: cbind(n_success, n_failure)
>>>
>>> Have you tried anova(your.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
>>> Belgium
>>>
>>> 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
>>>
>>>
>>> 2015-08-27 11:19 GMT+02:00 Mehdi Abedi <abedimail at gmail.com>:
>>>
>>>> Dear Thierry and Mariano,
>>>>
>>>> Could we apply these glmer for seed germination in petridishes which the
>>>> total number of seeds is defined as well? like cbind(seeds,100).
>>>>
>>>> In addition what is the simple way to get ANOVA liked tables (i think
>>>>
>>> with
>>>
>>>> Chisquare would be better test than F value) for these test with having
>>>>
>>> P-
>>>
>>>> value as well?
>>>> Warm regards,
>>>> Mehdi
>>>>
>>>> On Thu, Aug 27, 2015 at 12:20 PM, Thierry Onkelinx
>>>> <thierry.onkelinx at inbo.be> wrote:
>>>>
>>>>> Dear Mariano,
>>>>>
>>>>> The binomial distribution (not error family) assumes that you have a
>>>>> number of successes and failures. If the potential number of seeds is
>>>>> fixed by the morphology of the plant, then a binomial distribution is
>>>>> reasonable. If the potential number of seeds is dictated by
>>>>> morphology, then I'd rather see it as counts and use a Poisson or
>>>>> negative binomial.
>>>>>
>>>>> The correct syntax in the binomial case is cbind(success, failure). Or
>>>>> in your case cbind(seeds, 4 - seeds).
>>>>>
>>>>> 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
>>>>> Belgium
>>>>>
>>>>> 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
>>>>>
>>>>>
>>>>> 2015-08-26 20:32 GMT+02:00 Mariano Devoto <mdevoto at agro.uba.ar>:
>>>>>
>>>>>> Dear all. I am analysing data from a field experiment on a crop
>>>>>> pollination. I want to test if there are differences in the number of
>>>>>> seeds
>>>>>> per fruit between three treatments. The experimental design consists
>>>>>>
>>>>> of
>>>
>>>> four separate sites where small subplots (ca. 5 plants each) received
>>>>>> one
>>>>>> of the treatments. In each site, 8 subplots were allocated to
>>>>>>
>>>>> treatment
>>>
>>>> A,
>>>>>> 8 to treatment B and 4 to treatment C. When fruits were ripe I
>>>>>>
>>>>> collected
>>>
>>>> all plants from each subplot and counted stems, fruits per stem and
>>>>>> seeds
>>>>>> per fruit. I think a GLMM is the best way to go as I expect random
>>>>>> effects
>>>>>> related to field and subplot identity, and my response variable
>>>>>>
>>>>> (number
>>>
>>>> of
>>>>>> seeds) is clearly non-normal. My main concern is the choice of the
>>>>>>
>>>>> error
>>>
>>>> family. As I’m counting seeds I first though of a Poisson model, but
>>>>>> then
>>>>>> realized that seed numbers only range from 0 to 4. I am now
>>>>>>
>>>>> considering
>>>
>>>> using a binomial model such as this:
>>>>>>
>>>>>>
>>>>>> glmer(cbind(seeds,4) ~ treatment + (1|site) + (1|subplot),
>>>>>> data=seed.data,
>>>>>> family=binomial)
>>>>>>
>>>>>>
>>>>>> Does this make sense?
>>>>>>
>>>>>>
>>>>>> I would welcome any advice before hitting “SEND” in Tinn-R :-).
>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> *Mariano Devoto*
>>>>>>
>>>>>> [[alternative HTML version deleted]]
>>>>>>
>>>>>> _______________________________________________
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>>>>>> R-sig-ecology at r-project.org
>>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>>>>>>
>>>>> _______________________________________________
>>>>> R-sig-ecology mailing list
>>>>> R-sig-ecology at r-project.org
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>>>>>
>>>>
>>>>
>>>>
>>>> --
>>>>
>>>> Mehdi Abedi
>>>> Department of Range Management
>>>>
>>>> Faculty of Natural Resources & Marine Sciences
>>>>
>>>> Tarbiat Modares University (TMU)
>>>>
>>>> 46417-76489, Noor
>>>>
>>>> Mazandaran, IRAN
>>>>
>>>> mehdi.abedi at modares.ac.ir
>>>>
>>>> Homepage
>>>>
>>>> Tel: +98-122-6253101
>>>>
>>>> Fax: +98-122-6253499
>>>>
>>>
>>
>>
>
> --
>
> Bob O'Hara
>
> Biodiversity and Climate Research Centre
> Senckenberganlage 25
> D-60325 Frankfurt am Main,
> Germany
>
> Tel: +49 69 7542 1863
> Mobile: +49 1515 888 5440
> WWW: http://www.bik-f.de/root/index.php?page_id=219
> Blog: http://blogs.nature.com/boboh
> Journal of Negative Results - EEB: www.jnr-eeb.org
>
>
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>
--
*Mehdi Abedi Department of Range Management*
*Faculty of Natural Resources & Marine Sciences *
*Tarbiat Modares University (TMU) *
*46417-76489, Noor*
*Mazandaran, IRAN *
*mehdi.abedi at modares.ac.ir <Mehdi.abedi at modares.ac.ir>*
*Homepage
<http://www.modares.ac.ir/en/Schools/nat/Academic_Staff/~mehdi.abedi>*
*Tel: +98-122-6253101 *
*Fax: +98-122-6253499*
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