Larry Vernon Hedges Judd A. and Marjorie Weinberg College of Arts and Sciences, Weinberg Natural Sciences, Statistics

Larry Vernon Hedges

    Judd A. and Marjorie Weinberg College of Arts and Sciences
    Weinberg Natural Sciences
    Statistics
    Current Appointments:

    Professor; Statistics; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Professor; School of Education and Social Policy

    Professor; Institute for Policy Research; Research Centers and Institutes

    Chairperson; Statistics; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Board Of Trustees Professorship; Statistics; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Professor; Psychology; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Research Centers and Institutes
    Institute for Policy Research
    Current Appointments:

    Professor; Statistics; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Professor; School of Education and Social Policy

    Professor; Institute for Policy Research; Research Centers and Institutes

    Chairperson; Statistics; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Board Of Trustees Professorship; Statistics; Judd A. and Marjorie Weinberg College of Arts and Sciences

    Professor; Psychology; Judd A. and Marjorie Weinberg College of Arts and Sciences

Research Interest Keywords

Achievement Gap; Class Size Effects; Cognition & Models; Cognitive Science; Education Policy; Ethnic/Racial Disparities in Achievement; Evaluation; HLM (Hierarchical Linear Modeling); Measurement; Meta-Analyses; Quantitative Research Methods; Randomi

Office phone

847/491-8899

Email

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Effect sizes in three-level cluster-randomized experiments

Larry V. Hedges

(Profiled Author: Larry Vernon Hedges)

Journal of Educational and Behavioral Statistics. 2011;36(3):346-380.

Abstract

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies with other studies and to combine information across studies in meta-analyses. This article addresses the problem of defining effect sizes in designs with two levels of clustering and computing estimates of those effect sizes and their standard errors from information that is likely to be reported in journal articles. Five effect sizes are defined corresponding to different standardizations. Estimators of each effect size index are also presented along with their sampling distributions (including standard errors). © 2011 AERA.

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