[R] How to get the SS and MS from oneway.test?

[Rolf Turner]

It is not clear to me how meaningful sums of squares and mean squares
are in the context of oneway.test.().  Be that as it may, the short answer
is you ***can't*** get at them from the output of oneway.test().  The
oneway.test() function simply does not return enough information.

If you ***really*** want/need (or think you do!) SS and MS information,
you'll simply have to hack the code of oneway.test().  The code looks
simple enough.  I would advise reading the cited 1951 Biometrics paper
by Welch in conjunction with your code-hacking.

Good luck.

     cheers,

         Rolf Turner

On 10/04/12 14:16, lulumecindy wrote:
> Hello everyone:
>                              I'm a new member of this group.
>                              I have a question about "oneway.test".
>                              When I use "anova(lm(....))" to analysis the
> ANOVA,
>                              I can get the information about Sum Sq  and Mean
> Sq.
>                              (The R code and the results are as follows.)
>
>   >  anova(lm(BackCalac~factor(Assay),data=Control))
> Analysis of Variance Table
> Response: BackCalac
>                        Df  Sum Sq Mean Sq F value    Pr(>F)
> factor(Assay)  4 270.846  67.711  56.219 1.345e-10 ***
> Residuals     20  24.088   1.204
>
>                              But it default the variances are the same.
>                              If the variances aren't equal. I need to use the
> "oneway.test" method.
>                              Because oneway.test has the option about
> "var.equal=F".
>                              Here, I have a question about "oneway.test",
>                              How can I get "SS", and "MS" information from
> "oneway.test"?
>                              My R code and the results are as follows.
>                              Thank you very much.  :)
>
>> oneway.test(BackCalac~factor(Assay), var.equal=T,data=Control)
>          One-way analysis of means
> data:  BackCalac and factor(Assay)
> F = 56.2191, num df = 4, denom df = 20, p-value = 1.345e-10
>> oneway.test(BackCalac~factor(Assay), var.equal=F,data=Control)
>          One-way analysis of means (not assuming equal variances)
> data:  BackCalac and factor(Assay)
> F = 92.8834, num df = 4.000, denom df = 9.625, p-value = 1.165e-07
>
>
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