[R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?

[Jaime Ashander]

It's not a stand-alone resource, but Schielzeth and Nakagawa (2013) walks
through nested vs crossed. The paper has some nice graphics illustrating
the designs, and tables breaking down what is estimated in each, but no
example R code.


H Schielzeth, S Nakagawa (2013)  *Nested by design:model fitting and
interpretation in a mixed model era* *Methods in Ecology and Evolution*
 4:14-24. http://dx.doi.org/10.1111/j.2041-210x.2012.00251.x

- Jaime

On Fri, Nov 14, 2014 at 3:00 AM, <r-sig-mixed-models-request at r-project.org>
wrote:

> Date: Fri, 14 Nov 2014 13:51:45 +0330
> From: Mehdi Abedi <abedimail at gmail.com>
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Crossed and nested factors in experimental
>         designs: Are there any flowcharts for decision making?
> Message-ID:
>         <
> CADGhaghBEVKNYyRrhgStopbFTJxx4zNV+fG417jmGrAk-jwSBA at mail.gmail.com>
> Content-Type: text/plain; charset="UTF-8"
>
> Dear all,
>
> I am following your nice discussion in this group. Considering your high
> level discussion in this group i was not sure to ask basic problems in the
> mailing list!, therefore, i asked this question in researchgate.
>
> I think several researchers have this kind of question which your guidance
> can also help them using mixed models in their researches. I can imagine
> that teaching advanced statistic with simple language is not easy. However
> in addition to advanced statistic books and codes, introducing experimental
> design and their link to mixed models using simple codes would be valuable
> as well.
>
> It would be my pleasure to have your suggestion here or in this link:
>
> Warm regards
>
> Mehdi:
>
>
> https://www.researchgate.net/post/With_regards_to_crossed_and_nested_factors_in_experimental_designs_Are_there_any_flowcharts_for_decision_making
>
> Ecological researches mainly have complicated statistical design. Mixed
> models can test complicated designs with different crossed or nested
> factors. For instance lme4 and nlme could be used in R. However, still
> decision about statistical design is complicated for most researchers.
>
> Mixed models are quit an advanced method for most researchers and recent
> publications still use simple statistical designs. For instance most
> publications in high ranked journals related to plant ecophysiology and
> seed researches still apply only factorial design for the statistical
> analysis and not mixed models including random and fixed factors.
>
> Could you recommend some references or lectures introducing nested, crossed
> design with simple examples and simple codes in R?. I mean some simple
> explanation without details which start from simple design to complicated
> design like http://conjugateprior.org/2013/01/formulae-in-r-anova/
> <
> https://www.researchgate.net/go.Deref.html?url=http%3A%2F%2Fconjugateprior.org%2F2013%2F01%2Fformulae-in-r-anova%2F
> >
>
> Graphical designs showing these crossed and nested would also be useful.
> This information would be very helpful for both teachers and researchers
> for application correct statistical analysis.
>
> --
>
>
> *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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