best choice of GLMM for seed set data

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

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*

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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

Homepage

Tel: +98-122-6253101

Fax: +98-122-6253499