[R-sig-ME] strip plot design with pseudoreplication

[Javier Moreira]

hi, members of the group.

I'm trying to find the way to express a model within R.

My intention is to use a set of data from a wheat trial, harvested with GPS
mapping. I'm comparing the standard model that use the average of the plot
(experimental unit) vs. one that use every pseudo-replication (observation
unit-harvest point).

The design is a strip plot or split block, with 2 factors and 3 error
terms. For the first step, I use the Agricolae package.

model0_fijo = with(data21,strip.plot(BLOCK = BLOQUE,
                   COL = AMBIENTE,
                   ROW = TRATAMIENTO,
                   Y = RTO))
*data21, n=72
and this produces an anova with 3 error terms (Ea,Eb,Ec) and the correct
distribution of degrees of freedom (Ambiente, Ea/ Tratamiento,Eb/
interacción, Ec).

When I try to use the pseudo-replication, i first try to use lme(), and to
take into account the correct grouping, it produces 2 different Error
terms, and i get (Ambiente, Ea, and tratamamiento and interaction, Eb).
This makes the design as it was a split plot (2 error terms).

modelo2_MM<-lme(REND.~1+TRATAMIENTO*AMBIENTE,
                random=~1|BLOQUE/AMBIENTE/TRATAMIENTO,
                data=data1)
*data1, n=3095

According to a tutorial
<https://vsni.co.uk/case-studies/dealing-with-pseudo-replication-in-linear-mixed-models>for
the use of ASreml package i was able to use lmer() to account for the
block:plot interaction (1|BLOQUE:parcela) and get the same result as the
tutorial. But, this leaves the model with only 1 error term applied to
every factor and interaction. So, it takes into account the
pseudo-replication but not the correct error assign for the anova.

m2_lmer<-lmer(REND.~AMBIENTE*TRATAMIENTO+
        (1|BLOQUE)+(1|BLOQUE:AMBIENTE)+(1|BLOQUE:parcela),
       data=data1)

In the initial steps, to find a way with lmer() to get a 3 error model that
accounts for pseudo-replication would be great.
Following that, i also have to account for spatial correlation, and that
isn't an option within lmer() so, i have to get the same model translate to
lme().

Thanks a lot for your help. This data analysis is for a on farm trial from
my Msc thesis.

best regards,

Ing. Agr. Javier Moreira

-- 
Javier Moreira de Souza
Ingeniero Agrónomo
099 406 006

	[[alternative HTML version deleted]]