[R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?
abedimail at gmail.com
Fri Nov 14 18:26:13 CET 2014
Thanks for this nice article. In appendix authors suggested some R code as
On Fri, Nov 14, 2014 at 7:39 PM, Jaime Ashander <jashander at ucdavis.edu>
> 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?
>> 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
>> 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
>> 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,
>> 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/
>> 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>*
>> *Tel: +98-122-6253101 *
>> *Fax: +98-122-6253499*
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>> End of R-sig-mixed-models Digest, Vol 95, Issue 18
*Mehdi Abedi Department of Range Management*
*Faculty of Natural Resources & Marine Sciences *
*Tarbiat Modares University (TMU) *
*Mazandaran, IRAN *
*mehdi.abedi at modares.ac.ir <Mehdi.abedi at modares.ac.ir>*
*Tel: +98-122-6253101 *
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