# [R] Lack of independence in anova()

From: Phillip Good <pigood_at_verizon.net>
Date: Tue 05 Jul 2005 - 01:28:45 EST

If the observations are normally distributed and the 2xk design is balanced, theory requires that the tests for interaction and row effects be independent. In my program, appended below, this would translate to cntT (approx)= cntR*cntI/N if all R routines were functioning correctly. They aren't.

```  cntR=0
cntC=0
cntI=0
cntT=0
cntP=0
```

for(i in 1:N){
#generate data

v=gendata(size)
#analyze after build(ing) design containing data
```     lm.out=lm(yield~c*r,build(size,v))
av.out=anova(lm.out)

#if column effect is significant, increment cntC

if (av.out[[5]][1]<=p)cntC=cntC+1
#if row effect is significant, increment cntR
if (av.out[[5]][2]<=p){
cntR=cntR+1
tmp = 1
}
else tmp =0
if (av.out[[5]][3]<=p){
#if interaction is significant, increment cntI
cntI=cntI+1
#if both interaction and row effect are significant, increment cntT
cntT=cntT + tmp
}
}
```

list(cntC=cntC, cntR=cntR, cntI=cntI, cntT=cntT)
}
```col=c(rep(0,size[1]),rep(1,size[2]),rep(2,size[3]),rep(3,size[4]),
rep(0,size[5]),rep(1,size[6]),rep(2,size[7]),rep(3,size[8]))
row=c(rep(0,size[1]+size[2]+size[3]+size[4]),rep(1,size[5]+size[6]
```
+size[7]+size[8]))
return(data.frame(c=factor(col), r=factor(row),yield=v)) }

gendata=function(size){
ssize=sum(size);
return (rnorm(ssize))
}

#Example
size=c(3,3,3,0,3,3,3,0)
sim2(size,10000,10,.16)

Phillip Good
Huntington Beach CA

R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Jul 05 01:34:37 2005

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