I use an online calculator for between subjects t-tests, as my version of SPSS doesn't seem to offer effect sizes. I recollect checking what it did many years ago and it seemed to be accurate. So if anyone can point me to an online calculator for repeated measures effect sizes, I'd be most grateful.
I see several approaches here.
Online calculator paired t-test
If you are working from a t-test output, Lenhard & Lenhard's calculators help. Subheading number 4 provides a calculator for both paired and independent t-tests. You need to also know the correlation between the paired groups in order to calculate the effect size (I'm not sure if it returns Cohen's d or Cohen's dz, though).
Online calculator paired groups
If you have descriptive statistics for each group, you can plug them in Wiseheart's calculator. You need to also know the correlation between the paired groups in order to calculate the effect size (I'm not sure if it returns Cohen's d or Cohen's d4, though).
Hand calculation of Cohen's dz
An alternative approach, if you own the database, is to calculate the effect size by hand. The simplest way seems to be that provided by Cohen (eg, 1988), which chiefly ignores the correlation between paired groups but suffix for the case when such correlation is not known:
1) create a new variable of the differences between both groups (z = Time1 - Time2),
2) obtain the mean (Mz) and standard deviation (SDz) for this new variable,
3) divide Mz by SDz, which will give you the effect size for dependent groups (dz = Mz / SDz)
4) (Optional) For comparability purposes, Cohen's d = dz √2
Hand calculation of Cohen's d4
If the correlation between groups is known, then another alternative provided by Cohen (eg, 1988) is to calculate the effect size using the formula for d but correcting it by r.
1) d4 = (M1 - M2) / SD
2) Cohen's d = d4 / √(1 - r)
----
COHEN Jacob (1988). Statistical power analysis for the behavioral sciences (2nd ed). Psychology Press (New York, USA). ISBN 9780805802832.
LENHARD Wolfgang & Alexandra LENHARD (2014). Calculation of Effect Sizes. Retrieved from http://www.psychometrica.de/effect_size.html on 24 November 2014.
WISEHEART Melody (2013). Effect size calculator. Retrieved from http://www.cognitiveflexibility.org/effectsize/ on 24 November 2014.
http://www.psychometrica.de/effect_size.html
http://www.cognitiveflexibility.org/effectsize/
Maybe this could be helpful:
https://www.ai-therapy.com/psychology-statistics/effect-size-calculator
I recommend use the package "compute.es" in r.
Available here:
http://cran.r-project.org/web/packages/compute.es/index.html
I see several approaches here.
Online calculator paired t-test
If you are working from a t-test output, Lenhard & Lenhard's calculators help. Subheading number 4 provides a calculator for both paired and independent t-tests. You need to also know the correlation between the paired groups in order to calculate the effect size (I'm not sure if it returns Cohen's d or Cohen's dz, though).
Online calculator paired groups
If you have descriptive statistics for each group, you can plug them in Wiseheart's calculator. You need to also know the correlation between the paired groups in order to calculate the effect size (I'm not sure if it returns Cohen's d or Cohen's d4, though).
Hand calculation of Cohen's dz
An alternative approach, if you own the database, is to calculate the effect size by hand. The simplest way seems to be that provided by Cohen (eg, 1988), which chiefly ignores the correlation between paired groups but suffix for the case when such correlation is not known:
1) create a new variable of the differences between both groups (z = Time1 - Time2),
2) obtain the mean (Mz) and standard deviation (SDz) for this new variable,
3) divide Mz by SDz, which will give you the effect size for dependent groups (dz = Mz / SDz)
4) (Optional) For comparability purposes, Cohen's d = dz √2
Hand calculation of Cohen's d4
If the correlation between groups is known, then another alternative provided by Cohen (eg, 1988) is to calculate the effect size using the formula for d but correcting it by r.
1) d4 = (M1 - M2) / SD
2) Cohen's d = d4 / √(1 - r)
----
COHEN Jacob (1988). Statistical power analysis for the behavioral sciences (2nd ed). Psychology Press (New York, USA). ISBN 9780805802832.
LENHARD Wolfgang & Alexandra LENHARD (2014). Calculation of Effect Sizes. Retrieved from http://www.psychometrica.de/effect_size.html on 24 November 2014.
WISEHEART Melody (2013). Effect size calculator. Retrieved from http://www.cognitiveflexibility.org/effectsize/ on 24 November 2014.
http://www.psychometrica.de/effect_size.html
http://www.cognitiveflexibility.org/effectsize/
If you are looking repeated measures, you are looking a paired t-test case.
Basically you need to apply this formula: t* sqrt[(2(1-r)/n)]
where r is the correlation coefficient between the two groups and n is your sample size.
NOTE: n=n1=n2 (the two groups MUST have the same size)
I guess you can also use: t/sqrt(N )where N is your sample size.
Hello Andrew, I would use G*Power which is a free piece of software that you can download from the University of Dusseldorf http://www.gpower.hhu.de/en.html or PS: Power and Sample Size Calculation http://ps-power-and-sample-size-calculation.software.informer.com/ which is also free.
Dear Jose,
thanks very much for sharing this input, which was very helpful.
I was just wondering about the optional step you mention to translate dz scores into d scores for comparison (i.e. d = dz *√2), could you please point to some reference? I tried to work it out from the formulas but did not succeed.
Also, another paper that I found very helpful is by Daniel Lakens 2013:
http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/full
Cheers, David
http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/full
To follow up on this, I found this blog on different within subject ES measures very insightful:
http://jakewestfall.org/blog/index.php/2016/03/25/five-different-cohens-d-statistics-for-within-subject-designs/
Best,
David
Just seen your further reply - Thanks very much, David, very useful.
Cheers, Andrew
I think this http://www.socscistatistics.com/effectsize/Default3.aspx explains it well.
George
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