# [R] ANOVA test

peter dalgaard pdalgd at gmail.com
Fri Dec 26 16:55:31 CET 2014

```You could at least say that no, that is patently wrong! There are ways to reconstruct an ANOVA from means, sd, and group sizes, but this isn't it. In fact, the group sizes are not even used in the code.

I agree about the need for a statistical expert. Fundamental misunderstandings seem to be present.

-pd

> On 26 Dec 2014, at 16:23 , Bert Gunter <gunter.berton at gene.com> wrote:
>
> 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.glover at 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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>> and provide commented, minimal, self-contained, reproducible code.
>
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