[R-sig-ME] Error structure for split-split plot with treatment across blocks

[Elizabeth Graham]

Yes, good point, thank you!  That was explained to me by someone else as well, who recommended that I make my plots based on the coefficients of the model instead... do you, or anyone else reading this, know how to do that?  I think I will need to somehow combine or group coefficients by experimental level, for example, to make a Treatment-Shade interaction plot I will need a coefficient value for treatment-shaded, treatment-unshaded, control-shaded, and control-unshaded. 

Thanks again for your input, much appreciated.

Elizabeth
________________________________________
From: r-sig-mixed-models-bounces at r-project.org [r-sig-mixed-models-bounces at r-project.org] on behalf of S Ellison [S.Ellison at lgcgroup.com]
Sent: Wednesday, October 23, 2013 2:25 AM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Error structure for split-split plot with treatment across blocks

> -----Original Message-----
> From: Elizabeth Graham [mailto:sharon.graham at pg.canterbury.ac.nz]
> Sent: 21 October 2013 20:27
> m2<-lme(log(density)~Treatment*Shade*Leaves,
>                         random=~1|Stream/Shade/Leaves)
>
> was actually my original model structure, but has the same incongruity
> between model results and interaction plots - try
> interaction.plot(Shade, Treatment, density) for an example - the
> treatment and control lines do not intersect at all, and standard error
> bars do not overlap.

The default interaction.plot doesn't use the Stream random effect in its error bars; it's using the group means and standard errors based on assumed simple independent replication. Those 'replicates' aren't independent. That will tend to give underestimated standard errors compared to a correct nested random effects structure, as the Stream effect is quite big.

S Ellison


*******************************************************************
This email and any attachments are confidential. Any use...{{dropped:15}}