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EFFECTS AS CORRELATIONS

EFFECTS AS CORRELATIONS. EPSY 642- LECTURE 6 Meta Analysis FALL 2009 Victor L. Willson, Instructor. Computing Correlation Effect Sizes. Reported Pearson correlation- use that Regression b-weight: use t-statistic reported, e = t*(1/N E + 1/N C ) ½

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EFFECTS AS CORRELATIONS

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  1. EFFECTS AS CORRELATIONS EPSY 642- LECTURE 6 Meta Analysis FALL 2009 Victor L. Willson, Instructor

  2. Computing Correlation Effect Sizes • Reported Pearson correlation- use that • Regression b-weight: use t-statistic reported, e = t*(1/NE + 1/NC )½ • t-statistics: r = [ t2 / (t2 + dferror) ] ½ Sums of Squares from ANOVA or ANCOVA: r = (R2partial) ½ R2partial = SSTreatment/Sstotal Note: Partial ANOVA or ANCOVA results should be noted as such and compared with unadjusted effects

  3. Computing Correlation Effect Sizes • To compute correlation-based effects, you can use the excel program “Outcomes Computation correlations” • The next slide gives an example. • Emphasis is on disaggregating effects of unreliability and sample-based attenuation, and correcting sample-specific bias in correlation estimation • For more information, see Hunter and Schmidt (2004): Methods of Meta-Analysis. Sage. • Correlational meta-analyses have focused more on validity issues for particular tests vs. treatment or status effects using means

  4. Computing Correlation Effects Example

  5. Computing Correlation Effects Example

  6. Correcting correlations • r(corrected) = r*(1-r2)/(2N-2) • r(disattenuated) = r/sqrt(xy) • If only one reliability is reported, use that, assume other reliability is 1.0

  7. Weight Functions • For sample size correction, use N • For disattenuated correlations, use • w = (1/sr2)/xy • Where sr2 = (1-r2)/(N-1)

  8. Mediator Analysis • Use SPSS Regression analysis as with effect size analysis, with WLS, put in appropriate weight function as N or w

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