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9 - Effect Sizes in Cross-Cultural Research

Published online by Cambridge University Press:  05 June 2012

David Matsumoto
Affiliation:
San Francisco State University
Fons J. R. van de Vijver
Affiliation:
Universiteit van Tilburg, The Netherlands
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Summary

Effect sizes in cross-cultural research

Comparison* is a cornerstone of cross-cultural research. A standard methodology in conducting these comparisons begins with the selection of measures of psychological constructs that produce quantitative data from two or more cultures or countries. The usual statistical analysis of data from two cultures involves testing a null hypothesis (H0) that conflicts with the research hypothesis either by positing that a correlation between two variables is zero in the population or that there is no difference between the means of two populations. Differences are tested by comparing variance among the culture means relative to the variance within the cultures, typically using t or F tests. When the chance probability of obtaining t or F values is sufficiently low (≤5%), the result is considered statistically significant. The p level represents the probability that a result at least as extreme as the obtained result would occur if the H0 were true. This attained p value primarily indicates the strength of the evidence that the H0 is wrong (but the p value does not by itself indicate sufficiently how wrong H0 is).

Statistical significance does not necessarily reflect differences among people of the different cultures, however. The sole computation of ts or Fs precludes our ability to interpret meaningful differences among people, because p values merely indicate the strength of the evidence against the null hypothesis of no difference between population means. Statistical significance, assuming no Type I error, only reflects some unknown, nonzero difference between the population means. Furthermore, the larger the sample sizes, the easier it is for smaller differences to become statistically significant. Therefore, a statistically significant difference may actually reflect a trivially small difference between population means. Interpretations of cultural differences among people based on “statistically significant” findings may be based on “practically insignificant” differences between means. “Practically insignificant” means that the nonzero difference between culture means is so small that it is of little or no practical significance. A synonymous phrase would be “substantively insignificant.”

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Publisher: Cambridge University Press
Print publication year: 2010

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References

Abelson, R. P. 1997 On the surprising longevity of flogged horses: Why there is a case for the significance testPsychological Science 8 12CrossRefGoogle Scholar
Abu Libdeh, O. 1984 Strength of association in the simple general linear model: A comparative study of Hays’ omega-squaredUniversity of ChicagoChicagoGoogle Scholar
Bond, M. H.Tedeschi, J. T. 2001 Polishing the jade: A modest proposal for improving the study of social psychology across culturesMatsumoto, D.Handbook of culture and psychology309New YorkOxford University PressGoogle Scholar
Brant, R. 1990 Comparing classical and resistant outlier rulesJournal of the American Statistical Association 85 1083CrossRefGoogle Scholar
Carroll, R. M.Nordholm, L. A. 1975 Sampling characteristics of Kelley's22Educational and Psychological Measurement 35 541CrossRefGoogle Scholar
Cohen, J. 1962 The statistical power of abnormal–social psychological researchJournal of Abnormal and Social Psychology 65 145CrossRefGoogle ScholarPubMed
Cohen, J. 1988 Statistical power analysis for the behavioral sciencesNew YorkAcademic PressGoogle Scholar
Cole, P. M. 1986 Children's spontaneous control of facial expressionChild Development 57 1309CrossRefGoogle Scholar
Cole, P. M.Bruschi, C. J.Tamang, B. L. 2002 Cultural differences in children's emotional reactions to difficult situationsChild Development 73 983CrossRefGoogle ScholarPubMed
Dunlap, W. P. 1999 A program to compute McGraw and Wong's common language effect size indicatorBehavior Research Methods, Instruments, and Computers 31 706CrossRefGoogle ScholarPubMed
Ekman, P.Friesen, W. 1969 The repertoire of nonverbal behavior: Categories, origins, usage, and codingSemiotica 1 49CrossRefGoogle Scholar
Ezekiel, M. 1930 Methods of correlational analysisNew YorkWileyGoogle Scholar
Feingold, A. 1992 Sex differences in variability in intellectual abilities: A new look at an old controversyReview of Educational Research 62 61CrossRefGoogle Scholar
Feingold, A. 1995 The additive effects of differences in central tendency and variability are important in comparisons between groupsAmerican Psychologist 50 5CrossRefGoogle Scholar
Feingold, A.Mazzella, R. 1998 Gender differences in body image are increasingPsychological Science 9 190CrossRefGoogle Scholar
Fidler, F.Thompson, B. 2001 Computing correct confidence intervals for ANOVA fixed- and random-effects effect sizesEducational and Psychological Measurement 61 575Google Scholar
Fisher, R. A. 1925 Statistical methods for research workersLondonOliver & BoydGoogle Scholar
Grissom, R. J. 1994 Probability of the superior outcome of one treatment over anotherJournal of Applied Psychology 79 314CrossRefGoogle Scholar
Grissom, R. J. 2000 Heterogeneity of variance in clinical dataJournal of Consulting and Clinical Psychology 68 155CrossRefGoogle ScholarPubMed
Grissom, R.Kim, J. J. 2005 Effect sizes for research: A broad practical approachMahwah, NJErlbaumGoogle Scholar
Harris, R. J. 1997 Significance tests have their placePsychological Science 8 8CrossRefGoogle Scholar
Hays, W. L. 1994 Statistics for psychologistsFort Worth, TXHartcourt BraceGoogle Scholar
Hedges, L. V.Olkin, L. 1985 Statistical methods for meta-analysisSan Diego, CAAcademic PressGoogle Scholar
Hunter, J. E. 1997 Needed: A ban on the significance testPsychological Science 8 3CrossRefGoogle Scholar
Hunter, J. E.Schmidt, F. L. 2004 Methods and meta-analysisThousand Oaks, CASageCrossRefGoogle Scholar
Keselman, H. 1975 A Monte Carlo investigation of three estimates of treatment magnitude: Epsilon squared, eta squared, and omega squaredCanadian Psychological Review 16 44CrossRefGoogle Scholar
Levine, T. R.Hullett, C. R. 2002 Eta squared, partial eta squared, and misreporting of effect size in communication researchHuman Communication Research 28 612CrossRefGoogle Scholar
Loftus, G. R. 1996 Psychology will be a much better science when we change the way we analyze dataCurrent Directions in Psychological Science 5 161CrossRefGoogle Scholar
Mann, H. B.Whitney, D. R. 1947 On a test of whether one of two random variables is stochastically larger than the otherAnnals of Mathematical Statistics 18 50CrossRefGoogle Scholar
Matsumoto, D.Grissom, R.Dinnel, D. 2001 Do between-culture differences really mean that people are different? A look at some measures of cultural effect sizeJournal of Cross-Cultural Psychology 32 478CrossRefGoogle Scholar
Matsumoto, D.Takeuchi, S.Andayani, S.Kouznetsova, N.Krupp, D. 1998 The contribution of individualism–collectivism to cross-national differences in display rulesAsian Journal of Social Psychology 1 147CrossRefGoogle Scholar
Matsumoto, D.Yoo, S. H.Fontaine, J.Anguas-Wong, A. M.Arriola, M.Ataca, B.Bond, M. H.Boratav, H. B.Breugelmans, S. M.Cabecinhas, R.Chae, J.Chin, W. H.Comunian, A. L.DeGere, D. N.Djunaidi, A.Fok, H. K.Friedlmeier, W.Ghosh, A.Glamcevski, M.Granskaya, J. V.Groenvynck, H.Harb, C.Haron, F.Joshi, R.Kakai, H.Kashima, E.Khan, W.Kurman, J.Kwantes, C. T.Mahmud, S. H.Mandaric, M.Nizharadze, G.Odusanya, J. O. T.Ostrosky-Solis, F.Palaniappan, A. K.Papastylianou, D.Safdar, S.Setiono, K.Shigemasu, E.Singelis, T. M.Iva, P. S.Spieb, E.Sterkowicz, S.Sunar, D.Szarota, P.Vishnivetz, B.Vohra, N.Ward, C.Wong, S.Wu, R.Zebian, S.Zengeya, A. 2008 Mapping expressive differences around the world: The relationship between emotional display rules and Individualism v. CollectivismJournal of Cross-Cultural Psychology 39 55CrossRefGoogle Scholar
Matsumoto, D.Yoo, S. H.Hirayama, S.Petrova, G. 2005 Validation of an individual-level measure of display rules: The Display Rule Assessment Inventory (DRAIEmotion 5 23CrossRefGoogle Scholar
Maxwell, S. E.Camp, C. C.Arvey, R. D. 1981 Measures of strength of association: A comparative examinationJournal of Applied Psychology 66 525CrossRefGoogle Scholar
McGraw, K. O.Wong, S. P. 1992 A common language effect size statisticPsychological Bulletin 111 361CrossRefGoogle Scholar
Poortinga, Y. H.Van de Vijver, F. J. R.Joe, R. C.Van de Koppel, J. M. H. 1987 Peeling the onion called culture: A synopsisKagitcibasi, C.Growth and progress in cross-cultural psychology22Berwyn, PASwets North AmericaGoogle Scholar
Rosenthal, R. 1991 Meta-analytic procedures for social researchNewbury Park, CASageCrossRefGoogle Scholar
Rosenthal, R.Rosnow, R. L.Rubin, D. B. 2000 Contrasts and effect sizes in behavioral research: A correlational approachCambridgeCambridge University PressGoogle Scholar
Rosenthal, R.Rubin, D. B. 1982 A simple, general purpose display of magnitude of experimental effectJournal of Educational Psychology 74 166CrossRefGoogle Scholar
Rosenthal, R.Rubin, D. B. 1994 The counternull value of an effect size: A new statisticPsychological Science 5 329CrossRefGoogle Scholar
Saarni, C. 1979 Children's understanding of display rules for expressive behaviorDevelopmental Psychology 15 424CrossRefGoogle Scholar
Saarni, C. 1988 Children's understanding of the interpersonal consequences of nonverbal emotional-expressive behaviorJournal of Nonverbal Behavior 3 275CrossRefGoogle Scholar
Shrout, P. E. 1997 Should significance tests be banned? Introduction to a special section exploring the pros and consPsychological Science 8 1CrossRefGoogle Scholar
Staudte, R. G.Sheather, S. J. 1990 Robust estimation and testingNew YorkWileyCrossRefGoogle Scholar
Van de Vijver, F. J. R.Leung, K. 1997 Methods and data analysis for cross-cultural researchNewbury Park, CASageGoogle Scholar
Wilcox, R. R. 1997 Introduction to robust estimation and hypothesis testingSan Diego, CAAcademic PressGoogle Scholar
Wilcox, R. R. 1998 How many discoveries have been lost by ignoring modern statistical methods?American Psychologist 53 300CrossRefGoogle Scholar
Wilcox, R. R. 2001 Fundamentals of modern statistical methods: Substantially improving power and accuracyNew YorkSpringer-VerlagCrossRefGoogle Scholar
Wilcox, R. R. 2003 Applying contemporary statistical techniquesSan Diego, CAAcademic PressGoogle Scholar
Wilcoxon, F. 1945 Individual comparisons by ranking methodsBiometrics 1 80CrossRefGoogle Scholar
Wilkinson, L. 1999 Statistical methods in psychology journals: Guidelines and explanationsAmerican Psychologist 54 594CrossRefGoogle Scholar

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