This is a statistical question primarily and, as such, is off topic
here. Either consult a local statistical expert or post to a
statistical site like stats.stackexchange.com .
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll
On Fri, Dec 26, 2014 at 6:38 AM, Kristi Glover
<kristi.glo...@hotmail.com> wrote:
> Hi R user,
> I am wondering whether I can perform a simple ANOVA analysis in the data in
> which I have mean + SE (+- Standard Error) for several groups.
> For this one, I calculated upper and lower confidence interval and made
> three classes for each group (mean, upper and lower values). After that, I
> did ANOVA (simple Anova). I am wondering whether this is a wrong approach? I
> have given an example
>
>
> library(reshape)
> B<-structure(list(mean = c(0.0241262, 0.0433538, 0.2204764, 0.7830054
> ), SE = c(0.0209097, 0.0329281, 0.1003248, 0.3019256), site = structure(1:4,
> .Label = c("A",
> "B", "C", "D"), class = "factor")), .Names = c("mean", "SE",
> "site"), class = "data.frame", row.names = c(NA, -4L))
> attach(B)
> B1<-data.frame(B, Upper=mean+1.96*SE, Lower=mean-1.96*SE)
> B2<-subset(B1, select=c(-2))
> B2
> B3<-melt(B2, id=c("site"))
> B3
> Anova<-aov(B3$value~B3$site)
> summary(Anova)
>
> Thanks
>
>
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