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re: st: margins after split-plot anova

From   Luca Campanelli <>
To   "" <>
Subject   re: st: margins after split-plot anova
Date   Mon, 25 Jun 2012 03:27:35 +0100 (BST)

Thank you very much for your answer, David. 
The following command does the job: 
xtmixed depvar c.IQ group label label#group label#c.IQ, || id:, covariance(independent)

“margins” and “pwcompare” work fine after xtmixed, and I get correct margins after the model with or without the continuous covariate (still can’t get correct margins after anova with continuous covariate). 
Also I understand that xtmixed is a more flexible command. 

Thanks again

--------previous message---------

After skimming some books online I don't have full access to, like Analysis of Messy
Data Vol 3: Analysis of Covariance, it seems the problem with covariates in split plots 
is that the covariate could be measured at any of the different experimental units, 
and that has to be taken into account to get the model needed. The models are different
when the covariate is measured at different experimental units (plot or subplot).
What is not clear to me is how you could specify at what level the covariate is measured 
when you use the anova command in Stata. The alternative Stata command for mixed models 
is the xtmixed command, where covariates are explicitly specified at different levels in 
the syntax. You also get advantages of different correlations between units with that 

One source for adding a covariate to a split plot design is Chapter 11 in Variations on Split Plot and Split Block Experimental Designs (Wiley 2007).

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