[R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?
abedimail at gmail.com
Fri Nov 14 14:41:06 CET 2014
Thanks for your kind introducing this reference. I also read
"Biostatistical Design and Analysis Using R
A Practical Guide" by Logan which was very useful for statistical design.
Linking classical ANOVAs with mixed model is still confusing for me because
i have to collect information from different books (design from classic
book and mixed model from new books). Due to importance of random effects
in mixed model, misunderstanding designs can fully affect on analysis. I
worry to wrongly connect the basic experimental designs with mixed models.
Therefore, i asked group to introduce references talking about both
experimental design and mixed model in the same book or text avoiding this
On Fri, Nov 14, 2014 at 4:40 PM, Ben Bolker <bbolker at gmail.com> wrote:
> On 14-11-14 05:21 AM, Mehdi Abedi wrote:
> > 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
> > mailing list!, therefore, i asked this question in researchgate.
> > I think several researchers have this kind of question which your
> > can also help them using mixed models in their researches. I can imagine
> > that teaching advanced statistic with simple language is not easy.
> > in addition to advanced statistic books and codes, introducing
> > design and their link to mixed models using simple codes would be
> > as well.
> > It would be my pleasure to have your suggestion here or in this link:
> > Warm regards
> > Mehdi:
> > 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.
> It's pretty basic, but I like the section in Gotelli and Ellison's
> _Primer of Ecological Statistics_. They don't really get as far as
> crossed random effects, but they do discuss nested, randomized block,
> split-plot, and factorial (i.e. _crossed fixed effect_) designs.
> Ben Bolker
> R-sig-mixed-models at r-project.org mailing list
*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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