t.test() does give effect sizes: that is, it gives the actual difference
in means, and a confidence interval for this difference.
If you want to standardize your effect sizes you will have to do this
yourself. This is because the customs for standardization are different
in different fields. Many social sciences use the residual standard
deviation, but epidemiology and medicine typically use the measured units
(and where standardization is done, prefer to use %), and other
standardizations are possible.
It's quite possible that there are packages that do all of this for you.
If so, someone is likely to point them out.
-thomas
On Fri, 26 Oct 2007, Jenifer Larson-Hall wrote:
I'm just curious . . . if effect sizes are so important, and possibly a
better way of looking at results than p-values, since they don't depend
on effect size (Kline,2004; Murphy and Myors, 2004), why don't any of
the classical tests, like t.test or glht specified for Tukey's posthocs,
return effect sizes? I say classical because I'm sure there may be
packages out there, not in the base program, which do return effect
sizes, but do they also return everything glht does, which are
confidence intervals for mean differences, t-values and p-values,
standard error plus a cool MMC graph? Anyway, just wondering. I mean,
it's not that hard to calculate effect sizes on my own, but it seems
like if they were important they would be included . . .
Jenifer
Dr. Jenifer Larson-Hall
Assistant Professor of Linguistics
University of North Texas
(940)369-8950
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Thomas Lumley Assoc. Professor, Biostatistics
[EMAIL PROTECTED] University of Washington, Seattle
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
