Mixed ANCOVA with between-Ss covariate?

Hi all,

I have data from an experiment with 3 independent variables, 2 are
within and 1 is between. In addition to the dependent variable, I have
a covariate that is a single measure per subject. Below I provide an
example generated data set and my approach to implementing the ANCOVA.
However the output confuses me; why does the covariate only appear in
the first strata? Presumably it should appear in every strata in which
there can be between-Ss effects or interactions with between-Ss
effects, no?

#generate data
set.seed(1)
a=rbind(
       expand.grid(
               id=1:20
               ,iv1 = 1:2
               ,iv2 = 1:2
       )
)
a$group = factor(a$id<11)
a$dv = rnorm(length(a[,1]))
a$covariate = NA
for(i in unique(a$id)){
       a$covariate[a$id==i]= rnorm(1)
}

#make sure id, iv1, and iv2 are factorized
a$id=factor(a$id)
a$iv1=factor(a$iv1)
a$iv2=factor(a$iv2)

#run ANCOVA
covariate_aov = aov(dv~covariate+group*iv1*iv2+Error(id/(iv1*iv2)),data=a)
summary(covariate_aov)


--
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
www.thatmike.com

Looking to arrange a meeting? Check my public calendar:
http://www.thatmike.com/mikes-public-calendar

~ Certainty is folly... I think. ~

I'm surprised there were no takers on this query; I thought it would 
be an easy answer, particularly where I provided example data set and 
code.

Did my request run afoul of the list etiquette?

Hi all,

I have data from an experiment with 3 independent variables, 2 are
within and 1 is between. In addition to the dependent variable, I have
a covariate that is a single measure per subject. Below I provide an
example generated data set and my approach to implementing the ANCOVA.
However the output confuses me; why does the covariate only appear in
the first strata? Presumably it should appear in every strata in which
there can be between-Ss effects or interactions with between-Ss
effects, no?

#generate data
set.seed(1)
a=rbind(
	expand.grid(
		id=1:20
		,iv1 = 1:2
		,iv2 = 1:2
	)
)
a$group = factor(a$id<11)
a$dv = rnorm(length(a[,1]))
a$covariate = NA
for(i in unique(a$id)){
	a$covariate[a$id==i]= rnorm(1)
}

#make sure id, iv1, and iv2 are factorized
a$id=factor(a$id)
a$iv1=factor(a$iv1)
a$iv2=factor(a$iv2)

#run ANCOVA
covariate_aov = aov(dv~covariate+group*iv1*iv2+Error(id/(iv1*iv2)),data=a)
summary(covariate_aov)


-- 
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
www.thatmike.com

Looking to arrange a meeting? Check my public calendar:
http://www.thatmike.com/mikes-public-calendar

~ Certainty is folly... I think. ~