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Re: ANOVA Statistical Significance, where does "d" value come from?

Posted by bdates on Jan 30, 2019; 8:10pm
URL: http://spssx-discussion.165.s1.nabble.com/ANOVA-Statistical-Significance-where-does-d-value-come-from-tp5737341p5737351.html

Again, if anyone is interested, there's an unlocked copy of the Bagueli article at https://pdfs.semanticscholar.org/86b6/bef80331f6afbbcb7371bd23ab3abc3ba0b2.pdf



Brian Dates

From: SPSSX(r) Discussion <[hidden email]> on behalf of Bruce Weaver <[hidden email]>
Sent: Wednesday, January 30, 2019 2:44:09 PM
To: [hidden email]
Subject: Re: ANOVA Statistical Significance, where does "d" value come from?
 
But before you use d (or some other standardized effect size measure) as the
basis of a sample size estimate, see this short note by Russell Lenth:

  https://homepage.divms.uiowa.edu/~rlenth/Power/2badHabits.pdf

If you can get access to it, take a look at Thom Baguley's nice article too:

  https://onlinelibrary.wiley.com/doi/full/10.1348/000712608X377117

HTH.



bdates wrote
> There's an unlocked copy at
> http://www.bwgriffin.com/workshop/Sampling%20A%20Cohen%20tables.pdf
>
> A Power Primer Jacob Cohen Psychological Bulletin [PsycARTICLES]; July
> 1992; 112, 1; PsycARTICLES pg. 155 - Bryan W. Griffin's
> Web&lt;http://www.bwgriffin.com/workshop/Sampling%20A%20Cohen%20tables.pdf&gt;
> www.bwgriffin.com
> Reproduced with permission of the copyright owner. Further reproduction
> prohibited without permission. Created Date: 06/23/05 11:02
>
>
>
>
> Brian Dates
> ________________________________
> From: SPSSX(r) Discussion &lt;

> SPSSX-L@.UGA

> &gt; on behalf of Michael Palij &lt;

> mp26@

> &gt;
> Sent: Wednesday, January 30, 2019 1:55:03 PM
> To:

> SPSSX-L@.UGA

> Subject: Re: ANOVA Statistical Significance, where does "d" value come
> from?
>
> My bad.  When I go to the address I gave I have automatic access to
> the article (I guess I get it because I come from the
> nyu.edu&lt;http://nyu.edu&gt; domain but
> I don't remember acess being so seamless).  The full reference for the
> Cohen article is:
>
> Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159.
> doi:10.1037/0033-2909.112.1.155
>
> A Google search may turn up an unlocked copy (it is a popular
> article with over 32K citations according to Google Scholar).
>
> -Mike Palij
> New York University
>
>
>
> On Wed, Jan 30, 2019 at 1:11 PM Jon Peck &lt;

> jkpeck@

> &lt;mailto:

> jkpeck@

> &gt;> wrote:
> The Cohen article you cite is under lock and key.
>
> On Wed, Jan 30, 2019 at 10:27 AM Michael Palij &lt;

> mp26@

> &lt;mailto:

> mp26@

> &gt;> wrote:
> Note that, in general, there are two types of effect size measures:
> (1) Percentage of variance accounted for (e.g., eta-square, R-square, etc;
> historically, SPSS has peovided only this type of effect size measure).
> and
> (2) Difference(s) between means (e.g., d, g, f, etc.)
>
> Because of the critical role effect size measures play in statistical
> power
> analysis, one nice reference for effect size measures and power analysis
> is Jack Cohen's 1992 article "A Power Primer"; see:
> https://psycnet.apa.org/fulltext/1992-37683-001.html&lt;https://urldefense.proofpoint.com/v2/url?u=https-3A__psycnet.apa.org_fulltext_1992-2D37683-2D001.html&amp;d=DwMFaQ&amp;c=slrrB7dE8n7gBJbeO0g-IQ&amp;r=A8kXUln5f-BYIUaapBvbXA&amp;m=uzwM-Iuv5YnaMvgQ6gAPwXd3GrThLHAwnuRBlKIVaMQ&amp;s=ohZK9sN5vgraudfffyXbERUe65gbw65WLVTbFPs3JJM&amp;e=&gt;
>
> Note2:  For a one-way independent groups ANOVA, Cohen recommends
> the effect size measure "f".  However, in your example you only have two
> groups (which could have been analyzed by independent groups t-test),
> though f can be calculated, d is a simpler and more familiar measure.
> Cohen's Table 1 provides a listing of effect size measures, their
> formulas,
> and guidelines for the interpretation of the magnitude of an ES.
>
> HTH.
>
> -Mike Palij
> Nrw York University
>
>
> On Wed, Jan 30, 2019 at 11:01 AM William Peck &lt;

> peck@

> &lt;mailto:

> peck@

> &gt;> wrote:
> 5 months into learning SPSS / Statistics and need a hopefully quick primer
> on one statistic from ANOVA.
>
> I am duplicating a report from last year, which worked great for this
> year's data. SPSS ran great and I got the output I expected, but need help
> in interpreting last year's report.
>
> ANOVA output from last year is
>
> Fall CALC1  grades
>                         N       Mean            Std. Deviation
> Class of 2020   125     2.0720  1.01740
> Class of 2021   149     2.6644    .96989
> Total                   274     2.3942  1.03320
>
>
> Fall CALC1 grades
>                          SS             df      Mean Square     F     
> Sig.
> Between Groups  23.857  1       23.857  24.252  .000 ***
> Within Groups   267.573 272     .984
> Total                   291.431 273
>
> *** The footnote on this data says "There is a statistically significant
> and moderately sized (d = .60) difference in Calculus I grades between
> 2020 and 2021. "
>
> My question is where do you get "d = .60" (because I don't see it
> anywhere). If I can find that, at least I'll have a reference for the
> comment, then I'll study ANOVA myself and post questions as needed.
>
> (The statistician who did last year's report is nowhere to be found ...)
>
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> --
> Jon K Peck

> jkpeck@

> &lt;mailto:

> jkpeck@

> &gt;
>
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-----
--
Bruce Weaver
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