Date: Wed, 7 Sep 2005 16:17:32 +0200
Reply-To: Karl Koch <TheRanger@gmx.net>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Karl Koch <TheRanger@gmx.net>
Subject: Re: About effect sizes
Content-Type: text/plain; charset="iso-8859-1"
thank you for the information. I will follow the links and have a look to
the tools as well. I will also see if I can hold of this book. I have
general problems with the libraries here in order to get fast and cheap
access to books of this magnitude. This is my mean reason, why I look for
papers and examples or documentens that are freely available (e.g. written
for tutorials at universities).
My general problem here is really how to calculate effect size values. I
have already calculated partially eta squared (with SPSS), eta squared and
Cohen's f value for my design. However, I stuck at the point where I want to
know how much do factorial interactions affect the value of the main
effects. Also on the decision which effect size would be "best" (if this is
not a research question by itself)...
I would like to make an example:
I have three factors which are all significant. They all have non-trivial
(Cohen f / eta squared / partically eta squared) effect sizes (which is
good). However, I also have ongoing interactions between the effects.
Natuarally I wouild assume that I need to correct somehow those effects
sizes of the main effects in order to arrive at the real values that
represent the strengh of the factor. Those values would then allow to
estimate the impact of each of the three factors on the DV. I could then
say, for example, factor 1 was the strongest of my factors in terms of
increasing the score in my DV, factor 3 was second and factor 2 was third.
What really could help here would be a paper that used a factorial design
(preferably with more than two levels and more than two factors, but not
necessary) that applied effect sizes.
> --- Ursprüngliche Nachricht ---
> Von: Paul Ginns <firstname.lastname@example.org>
> An: SPSSX-L@LISTSERV.UGA.EDU
> Betreff: Re: About effect sizes
> Datum: Tue, 6 Sep 2005 14:28:47 +1000
> Hi Karl,
> a few suggestions for ANOVA effect sizes:
> Cohen's f is one effect size you can use, but there are others. The
> standardised mean difference (Cohen's d) can be scaled up to factorial
> Freeware which can be used to produce factorial d values, and confidence
> intervals around these d values, is available at
> http://www.psy.unsw.edu.au/research/PSY.htm and Kevin Bird has written a
book about this approach to
> ANOVA called
> Bird, K.D. (2004). Analysis of variance via confidence intervals. London:
> Sage Publications.
> Note that the above webpage also includes some SPSS syntax for calculating
> studentized maximum root product interaction contrasts.
> Another effect size is Epsilon squared. Jim Jaccard's Zumastat programme
> www.zumastat.com has a module that allows calcualtion of e-sq. and its CI
> using F values and degrees of freedom. (Note: I have no commercial
> in Zumastat.)
> Date: Mon, 5 Sep 2005 16:27:02 +0200
> From: Karl Koch <TheRanger@gmx.net>
> Subject: About Effect Sizes...
> Hello group,
> I have done a 3x3x2 factorial experiement which has significant main
> and interactions. The DV was a score between 1 (not useful) and 6 (very
> useful) on 6 levels. To know more about the magnitude of the three
> I was thinking of exploring the possibility to apply effect sizes. This
> would also spice up the experiment documentation.
> I found a, in my oppion good article in the Information Technology,
> Learning, and Performance Journal which is available online
> The article states that for Analysis of Variance (which applies to me) I
> should use Cohen's f effect size measure. Now my questions:
> 1) Can somebody here confirm that or does somebody here know other books
> articles (preferable also available online) which can help me to make a
> decent decision on that? I know that the entire topic is pretty strong
> discusses and some people disagree on what to choose. However, I am
> for a decent narrative what to use. Some examples (papers?) where people
> have used effect sizes in similar experiments would be helpful, too.
> 2) I have not only significant main effects but also significant
> interactions. How does this influence the meaning of the effect size
> measures of the meain effects.
> 3) If I want to find out the following: What is the most influcial factor
> (the one that influenced the DV most) ? Can I use the effect size measure
> determine that e.g. by determining that by choosing the main effect with
> greatest effect size?
> 4) Is there any other way to rank the three factors according their
> importance (in terms of influencing the DV by increasing the score)?
> Any help would be greatly appreciated.
> Kind Regards,
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