An effect is the result of something. It is an outcome, a result, a reaction, a change in Y brought about by a change in X.

An effect size refers to the magnitude of the result as it occurs, or would be found, in nature, or in a population. Although effects can be observed in the artificial setting of a laboratory or a sample, effect sizes exist in the real world.

When researchers estimate effect sizes by observing representative samples, they generate an effect size estimate. This estimate is usually expressed in the form of an effect size index.

For a good introduction to effect sizes – how to report them, how to interpret them – check out the e-book Effect Size Matters…

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The sign reveals the direction of the effect. A negative r indicates a negative correlation; a negative d indicates the effect is bigger for the second group.

I am not sure if you are checking this site.But can we use effect size to measure different measures? For example, we measure muscle growth via lean body mass, CSA, tape measure. So can we use effect size to combine these measurements and show the effect size?

Hi Paul, I was reading a meta-analysis about hypertrophy and it used effect size. And the author wrote this:

“Another problem with determining the effects of set volume on hypertrophy is the many ways in which hypertrophy can be measured. Studies have used wholebody lean mass (11,26), regional lean mass (27,35), muscle thickness (31,40), muscle cross-sectional area (31,35), or muscle circumference (30–32) to measure hypertrophy. Different regions of a particular muscle may also be measured (40). Thus, comparisons across studies can be difficult. The calculation of a standardized effect size (ES) can aid in the comparison across studies (3).”

From what I understand, he means effect size can be used to measure different measures of muscle growth and be compared. Is this true? If you are releasing a second edition , I have some suggestions.
Thanks!

Now I understand. This is the apples and and oranges problem I discuss on p.98 of the book. The author is interested in the effect of X (set volume – whatever that is) on Y (hypertrophy) but since the measurement of Y varies across studies, he is not sure that direct comparisons are possible. The solution he proposes (calculating standardized ES) does not deal with this particular problem but the problem of comparing results effects (not variables) that have been reported in different metrics.

Hi Paul, I checked page 98, but it didn’t say much. So are you saying we can use effect size as the author has used or you can’t? The measurements are in different units. I thought effect sizes measurements need to be for the same units.

Pages 99-101 discuss the reasons and methods for converting study-specific ES estimates into a common metric. Page 98 lists several tactics for making sure you don’t have an apples and oranges problem in the first place. If you need further information, any good meta-analysis textbook will have chapters on these issues. Some are listed in the Bibliography.

“The primary product of a research inquiry is one or more measures of effect size, not p values.”
~ Jacob Cohen

“Statistical significance is the least interesting thing about the results. You should describe the results in terms of measures of magnitude – not just, does a treatment affect people, but how much does it affect them.”
~ Gene Glass

What does a negative effect size tell me?

The sign reveals the direction of the effect. A negative

rindicates a negative correlation; a negativedindicates the effect is bigger for the second group.just ordered the book.

I am not sure if you are checking this site.But can we use effect size to measure different measures? For example, we measure muscle growth via lean body mass, CSA, tape measure. So can we use effect size to combine these measurements and show the effect size?

Thanks you

I think you are confusing the measurement of effects with the measurement of variables. Do you have a particular effect in mind?

Hi Paul, I was reading a meta-analysis about hypertrophy and it used effect size. And the author wrote this:

“Another problem with determining the effects of set volume on hypertrophy is the many ways in which hypertrophy can be measured. Studies have used wholebody lean mass (11,26), regional lean mass (27,35), muscle thickness (31,40), muscle cross-sectional area (31,35), or muscle circumference (30–32) to measure hypertrophy. Different regions of a particular muscle may also be measured (40). Thus, comparisons across studies can be difficult. The calculation of a standardized effect size (ES) can aid in the comparison across studies (3).”

From what I understand, he means effect size can be used to measure different measures of muscle growth and be compared. Is this true? If you are releasing a second edition , I have some suggestions.

Thanks!

Now I understand. This is the apples and and oranges problem I discuss on p.98 of the book. The author is interested in the effect of X (set volume – whatever that is) on Y (hypertrophy) but since the measurement of Y varies across studies, he is not sure that direct comparisons are possible. The solution he proposes (calculating standardized ES) does not deal with this particular problem but the problem of comparing results effects (not variables) that have been reported in different metrics.

Hi Paul, I checked page 98, but it didn’t say much. So are you saying we can use effect size as the author has used or you can’t? The measurements are in different units. I thought effect sizes measurements need to be for the same units.

Pages 99-101 discuss the reasons and methods for converting study-specific ES estimates into a common metric. Page 98 lists several tactics for making sure you don’t have an apples and oranges problem in the first place. If you need further information, any good meta-analysis textbook will have chapters on these issues. Some are listed in the Bibliography.