[R-sig-ME] Mixed model for count data with overdispersion

[Mehdi Abedi]

Thanks Chris for lectures,
Working with MCMCglmm is like jumping from high school physics to Albert
Einstein lectures:). Hopefully i can digest this as a ecologist this
modeling part!
All the best

On Mon, Aug 10, 2015 at 1:46 PM, Christopher David Desjardins <
cddesjardins at gmail.com> wrote:

> Hi,
>
> You really should read about the MCMCglmm package before just using it.
> There are a couple of vignettes which I strongly suggest that you read
> prior to actually using MCMCglmm as they explain a lot.
>
> https://cran.r-project.org/web/packages/MCMCglmm/vignettes/Overview.pdf
> https://cran.r-project.org/web/packages/MCMCglmm/vignettes/CourseNotes.pdf
>
> Do note that you need to specify prior distributions or at least
> understand the default ones.
>
> Chris
>
> On Aug 10, 2015, at 8:56 AM, Mehdi Abedi <abedimail at gmail.com> wrote:
>
> Thanks Manabu,
> It is a bit complicated for me but If i have this data:
> Parameter: Totalseedling
> fixed effect: Heatsmoke, cold
> random effect: plot
>
> I should do something like this?!
>
>
> Model1<- MCMCglmm(Totalseedling ~ Heatsmoke *Cold, random =
> ~Plots,family="poisson", data = growthdata)
> summary( Model1)
> It looks i can not get anova() here for output as well?
>
>
> I am not familiar with other details in the MCMCglmm:
>
> library( MCMCglmm)
> Model1<- MCMCglmm(Totalseedling ~ Heatsmoke *Cold, random = ~Plot,
> + family = "poisson", data = growthdata, prior = prior,
> + verbose = FALSE, pr = TRUE)
>
> Warm regards,
> Mehdi
>
> On Mon, Aug 10, 2015 at 12:48 PM, Manabu Sakamoto <
> manabu.sakamoto at gmail.com
>
> wrote:
>
>
> Dear Mehdi,
>
> You can use the function MCMCglmm in the package of the same name,
> specifying family="poisson". MCMCglmm automatically accounts for over
> dispersion in count data.
>
> best regards,
> Manabu
>
> On 10 August 2015 at 06:54, Mehdi Abedi <abedimail at gmail.com> wrote:
>
> Dear all,
>
> I had quick search but it looks there is no simple way in lme4 or  nlme In
> the case of overdispersion for count data,. How we can run mixed model for
> count data with family of quasipoisson or maybe NB?
>
> I my working on seeding emergence with 2 fixed factor (n=10) and i would
> like to have my plot as replicate(n=5) as a random.
>
> Warm regards,
> Mehdi
>
> --
>
>
> *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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>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
>
>
> --
> Manabu Sakamoto, PhD
> manabu.sakamoto at gmail.com
>
>
>
>
> --
>
>
> *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*
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
>


-- 


*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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