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 <boh...@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.onkel...@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 <abedim...@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.onkel...@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 <mdev...@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]] >>>>>> >>>>>> _______________________________________________ >>>>>> R-sig-ecology mailing list >>>>>> R-sig-ecology@r-project.org >>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology >>>>>> >>>>> _______________________________________________ >>>>> R-sig-ecology mailing list >>>>> R-sig-ecology@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.ab...@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 > > > _______________________________________________ > R-sig-ecology mailing list > R-sig-ecology@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.ab...@modares.ac.ir <mehdi.ab...@modares.ac.ir>* *Homepage <http://www.modares.ac.ir/en/Schools/nat/Academic_Staff/~mehdi.abedi>* *Tel: +98-122-6253101 * *Fax: +98-122-6253499* [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology