# Is er een overzicht van de tentatieve grenswaarden van effect sizes?

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Om te bepalen hoe sterk een effect of verband is, moet je naar effect sizes kijken, zoals Cohen's d, Pearson's r, $\eta^2$, of Cramèr's V. Is er ook ergens een overzicht van de grenswaarden voor deze effect sizes?

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Er zijn verschillende overzichten te vinden, maar een handige tabel staat op http://imaging.mrc-cbu.***.ac.uk/statswiki/FAQ/effectSize. Gemakshalve heb ik die hier even gepaste:

The scales of magnitude are taken from Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates. The scales of magnitude for partial $\omega^\text{2}$ are taken from Table 2.2 of Murphy and Myors (2004).

There is also a table of effect size magnitudes at the back of Kotrlik JW and Williams HA (2003). An overview of commonly used effect sizes in psychology is given by Vacha-Haase and Thompson (2004).

Kraemer and Thiemann (1987, p.54 and 55) use the same effect size values (which they call delta) for both intra-class correlations and Pearson correlations. This implies the below rules of thumb from Cohen (1988) for magnitudes of effect sizes for Pearson correlations could also be used for intra-class correlations. It should be noted, however, that the intra-class correlation is computed from a repeated measures ANOVA whose usual effect size (given below) is partial eta-squared. In addition, Shrout and Fleiss (1979) discuss different types of intra-class correlation coefficient and how their magnitudes can differ.

The general rules of thumb given by Cohen and Miles & Shevlin (2001) are for eta-squared, which uses the total sum of squares in the denominator, but these would arguably apply more to partial eta-squared than to eta-squared. This is because partial eta-squared in factorial ANOVA arguably more closely approximates what eta-squared would have been for the factor had it been a one-way ANOVA and it is presumably a one-way ANOVA which gave rise to Cohen's rules of thumb.

 Effect Size Use Small Medium Large Correlation 0.1 0.3 0.5 $\eta^2$ one-way anova (regression) 0.01 0.06 0.14 $\eta^2$ Anova 0.02 0.13 0.26 Anova; See Field (2013) 0.01 0.06 0.14 one-way MANOVA 0.01 0.06 0.14 Cohen's f one-way an(c)ova (regression) 0.10 0.25 0.40 $\eta^2$ Multiple regression 0.02 0.13 0.26 $\kappa^2$ Mediation analysis 0.01 0.09 0.25 Cohen's f Multiple Regression 0.14 0.39 0.59 Cohen's d t-tests 0.2 0.5 0.8 Cohen's $\omega$ chi-square 0.1 0.3 0.5 Odds Ratios 2 by 2 tables 1.5 3.5 9.0 Friedman test 0.1 0.3 0.5

Also:Haddock et al (1998) state that $\sqrt{3/\pi}$ multiplied by the log of the odds ratio is a standardised difference equivalent to Cohen's d.

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Is iemand hier ook iets bekend over de waarde van van de partial eta square? Kwam wel ergens iets tegen over dat deze gelijk zijn aan eta square als er slechts één onafhankelijke variabele is, maar uiteraard kan ik dit nergens meer terugvinden/nazoeken...