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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