Skip to main content Accessibility help

Averaging Dependent Effect Sizes in Meta-Analysis: a Cautionary Note about Procedures

  • Fulgencio Marín-Martínez (a1) and Julio Sánchez-Meca (a1)


When a primary study includes several indicators of the same construct, the usual strategy to meta-analytically integrate the multiple effect sizes is to average them within the study. In this paper, the numerical and conceptual differences among three procedures for averaging dependent effect sizes are shown. The procedures are the simple arithmetic mean, the Hedges and Olkin (1985) procedure, and the Rosenthal and Rubin (1986) procedure. Whereas the simple arithmetic mean ignores the dependence among effect sizes, both the procedures by Hedges and Olkin and Rosenthal and Rubin take into account the correlational structure of the effect sizes, although in a different way. Rosenthal and Rubin's procedure provides the effect size for a single composite variable made up of the multiple effect sizes, whereas Hedges and Olkin's procedure presents an effect size estimate of the standard variable. The three procedures were applied to 54 conditions, where the magnitude and homogeneity of both effect sizes and correlation matrix among effect sizes were manipulated. Rosenthal and Rubin's procedure showed the highest estimates, followed by the simple mean, and the Hedges and Olkin procedure, this last having the lowest estimates. These differences are not trivial in a meta-analysis, where the aims must guide the selection of one of the procedures.

La estrategia usual para integrar meta-analíticamente los múltiples tamaños del efecto cuando un estudio primario incluye varios indicadores del mismo constructo, es la de promediarlos. En este trabajo se muestran las diferencias numéricas y conceptuales entre tres procedimientos para promediar tamaños del efecto dependientes. Los procedimientos son el de Hedges y Olkin (1985), el de Rosenthal y Rubin (1986) y el de la media aritmética. Mientras que el de la media aritmética ignora la dependencia entre los tamaños del efecto, tanto el de Hedges y Olkin como el de Rosenthal y Rubin tienen en cuenta, aunque de diferente forma, la estructura correlacional de los tamaños del efecto. El procedimiento de Rosenthal y Rubin proporciona el tamaño del efecto de una sola variable compuesta, obtenida a partir de los diversos tamaños del efecto, mientras que el de Hedges y Olkin aporta una estimación del efecto para la variable estándar. Los tres procedimientos se aplicaron a 54 condiciones, manipulándose la magnitud y homogeneidad del vector de los tamaños del efecto y de la matriz de correlaciones entre ellos. Con el procedimiento de Rosenthal y Rubin se obtuvieron las estimaciones más elevadas, seguido del de la media y del de Hedges y Olkin. Estas diferencias no son triviales en un meta-análisis, cuyos objetivos son los que deben guiar la elección de uno u otro de los procedimientos.


Corresponding author

Correspondence concerning this article should be addressed to Dr. Fulgencio Marín-Martínez, Departamento de Psicología Básica y Metodología. Facultad de Psicología.Universidad de Murcia. Campus de Espinardo, Apdo 4021. 30080 Murcia (Spain). E-mail:


Hide All
Abrami, P.C., Cohen, P.A., & d'Apollonia, S. (1988). Implementation problems in meta-analysis. Review of Educational Research, 58, 151179.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
Cooper, H.M. (1989). Integrating research: A guide for literature reviews (2nded.). Beverly Hills, CA: Sage.
GAUSS (1992). The GAUSS System (Vers. 3.0). Washington: Aptech Systems, Inc.
Glass, G.V., McGaw, B., & Smith, M.L. (1981). Meta-analysis in social research. Beverly Hills, CA: Sage.
Gleser, L.J., & Olkin, I. (1994). Stochastically dependent effect sizes. In Cooper, H.M. & Hedges, L.V. (Eds.), The handbook of research synthesis (pp. 339355). New York: Sage.
Hedges, L.V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL: Academic Press.
Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis: Correcting error and bias in research findings. Beverly Hills, CA: Sage.
Johnson, B. T., & Eagly, A. H. (in press). Quantitative synthesis of social psychological research. In Reis, H.T. & Judd, C.M. (Eds.), The handbook of research methods in social psychology. London: Cambridge University Press.
Kalaian, H.A., & Raudenbush, S.W. (1996). A multivariate mixed linear model for meta-analysis. Psychological Methods, 1, 225235.
Marascuillo, L.A., Busk, P.L., & Serlin, R.C. (1988). Large sample multivariate procedures for comparing and combining effect sizes within a single study. Journal of Experimental Education, 58, 6985.
Marín-Martínez, F., & Sánchez-Meca, J. (1998). Testing for dichotomous moderators in meta-analysis. Journal of Experimental Education, 67, 6981.
Matt, G.E. (1989). Decision rules for selecting effect sizes in meta-analysis: A review and reanalysis of psychotherapy outcome studies. Psychological Bulletin, 105, 106115.
Matt, G.E., & Cook, T.D. (1994). Threats to the validity of research syntheses. In Cooper, H.M. & Hedges, L.V. (Eds.), The handbook of research synthesis (pp. 503520). New York: Sage.
Raudenbush, S.W., Becker, B.J., & Kalaian, H. (1988). Modeling multivariate effect sizes. Psychological Bulletin, 103, 111120.
Rosenthal, R. (1991). Meta-analytic procedures for social research (rev. ed.). Newbury Park, CA: Sage.
Rosenthal, R. (1994). Parametric measures of effect size. In Cooper, H.M. & Hedges, L.V. (Eds.), The handbook of research synthesis (pp. 231244). New York: Sage.
Rosenthal, R. (1995). Writing meta-analytic reviews. Psychological Bulletin, 118, 183192.
Rosenthal, R., & Rubin, D.B. (1986). Meta-analytic procedures for combining studies with multiple effect sizes. Psychological Bulletin, 99, 400406.
Sánchez-Meca, J., & Ato, M. (1989). Meta-análisis: Una alternativa metodológica a las revisiones tradicionales de la investigación. In Arnau, J. & Carpintero, H. (Eds.), Tratado de psicología general. I: Historia, teoría y método (pp. 617669). Madrid: Alhambra.
Sánchez-Meca, J., & Marín-Martínez, F. (1997). Homogeneity tests in meta-analysis: A Monte Carlo comparison of statistical power and Type I error. Quality and Quantity, 31, 385399.
Sánchez-Meca, J., & Marín-Martínez, F. (1998a). Weighting by inverse-variance or by sample size in meta-analysis: A simulation study. Educational and Psychological Measurement, 58, 211220
Sánchez-Meca, J., & Marín-Martínez, F. (1998b). Testing continuous moderators in meta-analysis: A comparison of procedures. British Journal of Mathematical and Statistical Psychology, 51, 311326.


Averaging Dependent Effect Sizes in Meta-Analysis: a Cautionary Note about Procedures

  • Fulgencio Marín-Martínez (a1) and Julio Sánchez-Meca (a1)


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed