Larry V. Hedges
Board of Trustees Professor of Statistics and Education and Social Policy | Professor of Psychology | Professor of Medical Social Sciences | Director of the IPR Q-Center
A national leader in the fields of educational statistics and evaluation, Larry V. Hedges joined the Northwestern faculty in 2005. He is one of eight Board of Trustees Professors at Northwestern, the university’s most distinguished academic position. He holds appointments in statistics, psychology, and education and social policy. Previously, he was the Stella M. Rowley Distinguished Service Professor at the University of Chicago.
Hedges’ research straddles many fields—in particular those of sociology, psychology, and educational policy. He is best known for his work to develop statistical methods for meta-analysis (a statistical analysis of the results of multiple studies that combines their findings) in the social, medical, and biological sciences. It is a key component of evidence-based social research. Examples of some his recent studies include: understanding the costs of generating systematic reviews, differences between boys and girls in mental test scores, the black-white gap in achievement test scores, and frameworks for international comparative studies on education.
Widely published, he has authored or co-authored numerous journal articles and eight books, including the seminal Statistical Methods for Meta-Analysis (with I. Olkin, Elsevier, 1985) and The Handbook of Research Synthesis and Meta-Analysis (with H. Cooper and J. Valentine, Russell Sage, 2009).
He is an elected member of the National Academy of Education and is a fellow of the American Academy of Arts and Sciences, the American Statistical Association, the American Psychological Association, and the American Educational Research Association. He is a member of the National Education Sciences Board and was president of the Society for Research on Educational Effectiveness, which he helped found. He was nominated by President Barack Obama to the Board of Directors of the National Board for Education Sciences and was confirmed by the U.S. Senate in June 2012. He was elected "Statistician of the Year" by the Chicago chapter of the American Statistical Association for 2013–14.
Training Institute on Randomized Controlled Trials in Education Research. Funded by the U.S. Department of Education's Institute of Education Sciences, this project, now in its tenth year, provides an intensive two-week summer institute for research professionals who desire advanced training in the design, conduct, and analysis of large-scale randomized experiments in education.
The Social Distribution of Academic Achievement in America. In this project that receives funding from the Spencer Foundation, Hedges and his colleagues seek to document the social distribution of academic achievement in the United States. By examining various achievement gaps (by gender, race, ethnicity, social class, etc.) in different ways, they come to understand how the social distribution of achievement has changed over the last few decades. A major part of this study evaluates patterns of between- and within-school variability of student achievement. They also examine whether different sources of evidence lead to the same conclusions, that is, they seek to triangulate whenever possible. Finally, the researchers study the—somewhat limited—longitudinal evidence, attempting to coordinate it with repeated cross-sectional evidence. They expect that combining such data may help us understand the emergence of differences in patterns of academic achievement between important population sub-groups. How large, for example, are achievement gaps when students enter school? How do these gaps grow over time? How does social context and school context affect the initial gaps and their growth over time? Do between-school differences grow over time and what is associated with this growth?
State-specific Design Parameters for Designing Better Evaluation Studies. This project, supported by IES, seeks to use state assessment data systems to estimate design parameters (such as variance component and intraclass correlation structures across school districts, schools, and classrooms) for use in multi-level study designs in education. This includes work on how these design parameters differ across states. In addition, it is developing empirical evidence on other parameters that serve as checks on plausibility of design parameters (such as effect sizes and variance of treatment effects) that are important but cannot be estimated directly from survey or census data.
Improving the Generalizability of Evaluation Research. This project, supported by grants from the National Science Foundation and the Spencer Foundation, supports a program of work on methods to formalize subjective notions of generalizability and external validity. This includes theoretical work on the quantification of generalizability concepts in terms of bias and variance of estimates of population average treatment effect. It also includes developing methods for better generalization from existing experiments, case studies of retrospective generalizability, and methods for better planning of education experiments for generalization to policy-relevant populations.
Do Research Prizes Have Effects on Minorities' Biomedical Research Careers? Research prizes are ubiquitous in science, but it is unclear whether they have effects on scientists career, and if so, the mechanism by which they produce effects. With funding from the National Institute of General Medical Sciences, this study of a national undergraduate research prize competition for minority students aims to understand the mechanism by which research prizes affect undergraduate minority students’ career success as scholars. Success includes pursuing and completing graduate training in the biomedical sciences and subsequent career accomplishments.
Methods to Protect Privacy in State Longitudinal Data Systems Research Files. The U.S. Institute of Education Sciences (IES) has spent over $600 million helping states develop longitudinal data systems to better understand (and improve) the functioning of American school systems, yet researchers face barriers to access of state longitudinal data systems due to concerns about protecting privacy and the Federal Education Rights and Privacy Act (FERPA). In this project, funded by the Spencer Foundation, IES, and NSF, and with the cooperation of over a dozen states, we are investigating methods to make large datasets available while protecting the privacy of individuals included in those datasets.
Books and Monographs
Cooper, H. M., L. V. Hedges, and J. Valentine, eds. 2009. The Handbook of Research Synthesis and Meta-Analysis, 2nd ed. New York: The Russell Sage Foundation.
Borenstein, M., L. V. Hedges, J. P. T. Higgins, and H. R. Rothstein. 2009. Introduction to Meta-Analysis. London: Wiley.
Hedges, L. V., and B. Schneider, eds. 2005. The Social Organization of Schooling. New York: The Russell Sage Foundation.
Cook, T., H. M. Cooper, D. Cordray, L. V. Hedges, R. J. Light, T. Louis, and F. Mosteller. 1994. Meta-Analysis for Explanation. New York: The Russell Sage Foundation.
Cooper, H. M. and L. V. Hedges, eds. 1993. The Handbook of Research Synthesis. New York: The Russell Sage Foundation.
Draper, D., D. P. Gaver, P. K. Goel, J. B. Greenhouse, L. V. Hedges, C. N. Morris, J. R. Tucker, and C. Waternaux. 1993. Combining Information: Statistical Issues and Opportunities for Research. Washington, D.C.: American Statistical Association.
Hedges, L. V., J. A. Shymansky, and G. Woodworth. 1989. A Practical Guide to Modern Methods of Meta-Analysis. Washington, D.C.: National Science Teachers Association.
Hedges, L. V., and I. Olkin. 1985. Statistical Methods for Meta-Analysis. New York: Academic Press.
Selected Journal Articles
Hedges, L. V., and I. Olkin. 2016. Overlap between treatment and control group distributions of an experiment as an effect size measure. Psychological Methods 21: 61-68.
Hedges, L. V. 2016. Applying meta-analysis to structural equation modeling. Journal of Research Synthesis Methods 7: 209-214.
Tipton, E., L. V. Hedges, K. Hallberg, and W. Chang. 2016. Implications of small samples for generalization: Adjustments and rules of thumb. Evaluation Review 40: 1-34.
O'Muircheartaigh, C., and L. V. Hedges. 2014. Generalizing from experiments with non-representative samples. Journal of the Royal Statistical Society, Series C 63: 195–210.
Pustejovsky, J. E., L. V. Hedges, and W. L. Shadish. 2014. Design-comparable effect sizes in multiple baseline designs: A general modeling framework. Journal of Educational and Behavioral Statistics 39: 368-393.
Hedges, L. V., and M. Borenstein. 2014. Constrained optimal design in three and four level experiments. Journal of Educational and Behavioral Statistics 39: 257–81.
Hedges, L. V., J. Pustejovsky, and W. Shadish. 2013. A standardized mean difference effect size for multiple baseline designs. Journal of Research Synthesis Methods 4: 324–41.
Hedges, L. V., J. Pustejovsky, and W. Shadish. 2012. A standardized mean difference effect size for single case designs. Journal of Research Synthesis Methods 3: 224–39.
Hedges, L. V. 2011. Effect sizes in three level designs. Journal of Educational and Behavioral Statistics 36: 346–80.
Hedges, L. V., and C. Rhoads. 2011. Correcting an analysis of variance for clustering. British Journal of Mathematical and Statistical Psychology 64: 20–37.
Hedges, L. V., E. Tipton, and M. Johnson. 2010. Robust variance estimation for meta-regression with dependent effect size estimators. Journal of Research Synthesis Methods 1: 39–65.
Hedges, L. V., and C. Rhoads. 2010. Statistical power analysis. In International Encyclopedia of Education, ed. B. McGaw, E. Baker, and P. Peterson, 436–43. Oxford: Elsevier
Hedges, L. V. 2009. Adjusting a significance test for clustering in designs with two levels of nesting. Journal of Educational and Behavioral Statistics 34: 464–90.
Hedges, L. V., and E. Hedberg. 2007. Interclass correlation values for planning group-randomized trials in education. Educational Evaluation and Policy Analysis 29(1): 60–87.
Hedges, L. V. 2007. Correcting a significance test for clustering. Journal of Educational and Behavioral Statistics 32(2): 151–79.
Hedges, L. V. 2007. Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics. 32(4): 341–70.
Hedges, L. V. 2007. Meta-analysis. In The Handbook of Statistics, ed. C. Rao, 919–53. Amsterdam: Elsevier.
Hedges, L. V., and J. Vevea. 2005. Selection model approaches to publication bias. In Publication Bias in Meta-Analysis, ed. H. Rothstein, A. Sutton, and M. Borenstein, 145–74. New York: Wiley.
Hedges, L. V., and T. D. Pigott. 2004. The power of statistical tests for moderators in meta-analysis. Psychological Methods 9:426–45.
Hedges, L. V., and T. D. Pigott. 2001. The power of statistical tests in meta-analysis. Psychological Methods 6:203–17.
Hirsch, B., L. V. Hedges, J. Stawicki, and M. Mekinda. 2015. The impact of After School Matters on positive youth development, academic, and problem behavior. In Job Skills and Minority Youth: New Program Directions, ed. by B. Hirsch, 127-159. New York: Cambridge University Press.
Hedges, L. V., and E. Hedberg. 2013. Intraclass correlations and covariate outcome correlations for planning two- and three-level cluster-randomized experiments in education. Evaluation Review 37: 13–57.
Hedges, L. V. 2013. Recommendations for practice: Justifying claims of generalizability. Educational Psychology Review 25(3): 331–37.
Hedges, L. V., and N. Jones. 2012. Research infrastructure for improving urban education. In Research on Schools, Neighborhoods, and Communities: Toward Civic Responsibility, ed. W. F. Tate IV, 481–504. New York: Rowan and Littelfield.
Hedges, L. V., J. Hanis, and E. Asch. 2011. Statistical evaluations of Spencer fellowship programs. In Learning to work better, ed. M. McPherson, 9–26. Chicago: The Spencer Foundation.
Hedges, L. V., and J. Hanis. 2009. Can non-randomized studies provide evidence of causal effects? A case study using the regression discontinuity design. In Education Research on Trial, ed. P. B. Walters, A. Lareau, and S. H. Ranis. New York: Routledge.
Konstantopoulos, S., and L. V. Hedges. 2008. How large an effect can we expect from school reforms? Teachers College Record 110(8): 1611–38.
Hedges, L. V., and E. Hedberg. 2007. Interclass correlation values for planning group-randomized trials in education. Educational Evaluation and Policy Analysis 29(1): 60–87.
Nye, B., L. V. Hedges, and S. Konstantopoulos. 2004. How large are teacher effects? Educational Evaluation and Policy Analysis 26:237–57.
Nye, B., L. V. Hedges, and S. Konstantopoulos. 2004. Do minorities experience greater lasting benefits from small classes?: Evidence from a five year follow-up of the Tennessee class size experiment. Journal of Educational Research 97:94-100.
Hedges, L. V., S. Konstantopoulos, and A. Thoreson. 2003. Studies of technology implementation and effects. In Evaluating educational technology: Effective research designs for improving learning, ed. G. D. Haertel and B. Means, 187–204. New York: Teachers College Press.
Nye, B., L. V. Hedges, and S. Konstantopoulos. 2002. Do low achieving students benefit more from small classes?: Evidence from the Tennessee class size experiment. Educational Evaluation and Policy Analysis 24:201-17.
Nye, B., L. V. Hedges, and S. Konstantopoulos. 2000. The effects of small classes on achievement: The results of the Tennessee class-size experiment. American Educational Research Journal 37:123–51.
Nye, B., L. V. Hedges, and S. Konstantopoulos. 2000. Do minorities and the disadvantaged benefit more from small classes?: Evidence from the Tennessee class-size experiment. American Journal of Education 109:1–26.
Nye, B., L. V. Hedges, and S. Konstantopoulos. 1999. The long-term effects of small classes: A five-year follow-up of the Tennessee class-size experiment. Educational Evaluation and Policy Analysis 21:127–42.
Goldin-Meadow, S., S. Levine, L. V. Hedges, J. Huttenlocher, S. Raudenbush, and S. Small. 2014. New evidence about language and cognitive development based on a longitudinal study. American Psychologist 69(6): 588–99.
Huttenlocher, J., W. Waterfall, M. Vasilyeva, J. Vevea, J., and L . V. Hedges. 2010. Sources of variability in children’s language growth. Cognitive Psychology 61: 343–65.
Duffy, S., J. Huttenlocher, L. V. Hedges, and L. Crawford. 2010. Category effects on stimulus estimation: Shifting and skewed frequency distributions. Psychonomic Bulletin & Review 172: 224–30.
Huttenlocher, J., L. V. Hedges, E. Crawford, and B. Corrigan. 2007. Estimating stimuli in contrasting categories: Truncations due to boundaries. Journal of Experimental Psychology 136(3): 502–19.
Huttenlocher, J., M. Vasilyeva, J. Vevea, and L. V. Hedges. 2007. Varieties of speech in young children. Developmental Psychology 43(5): 1062–83.
Crawford, E., J. Huttenlocher, and L. V. Hedges. 2006. Within-category feature correlations and Bayesian adjustment strategies. Psychonomic Bulletin and Review 13:245-50.
Klibanoff, R., S. C. Levine, J. Huttenlocher, M. Vasilyeva, and L. V. Hedges. 2006. Preschool children’s mathematical knowledge: The effect of teacher input. Developmental Psychology 42:59-69.
Huttenlocher, J., L. V. Hedges, B. Corrigan, and E. Crawford. 2004. Spatial categories and the estimation of location. Cognition 93:75–97.
Huttenlocher, J., L. V. Hedges, and J. L. Vevea. 2000. Why do categories affect stimulus judgment? Journal of Experimental Psychology 129:1–22.
Konstantopoulos, S., M. Modi, and L. V. Hedges. 2001. Who are America’s gifted? American Journal of Education 109:344–82.
Hedges, L. V., and A. Nowell. 1999. Changes in the black-white gap in achievement test scores: The evidence from nationally representative samples. Sociology of Education 72:111–35.
Nowell, A., and L. V. Hedges. 1998. Trends in gender differences in academic achievement from 1960 to 1994: An analysis of differences in mean, variance and extreme scores. Sex Roles 39:21–43.
Hedges, L. V., and A. Nowell, A. 1998. Are black-white differences in test scores narrowing? in The Black White Test Score Gap, ed. C. Jencks and M. Phillips, 254-81. Washington, DC: The Brookings Institution.
Research in Biology, Medicine or Public Health Publications
Bilimoria, K., J. Chung, L. V. Hedges, et al. 2016. The flexibility in duty hour requirements for surgical trainees (FIRST) trial: A national randomized trial of resident duty hour policies. The New England Journal of Medicine 374: 713-727.
Hedges, L. V. 2011. Comment on multivariate meta-analysis. Statistics in Medicine 39: 2499.
Hedges, L. V., and E. Tipton. 2010. Meta-analysis in behavioral medicine. In The Handbook of Behavioral Medicine,ed. A. Steptoe, 909-21. London: Springer-Verlag.
Mullen, P. D., G. Ramírez, D. Strouse, L. V. Hedges, and E. Sogolow. 2002. Meta-analysis of the effects of behavioral HIV prevention interventions on the sexual risk behavior of sexually experienced adolescents in U.S.-controlled studies. Journal of Acquired Immune Deficiency Syndromes 30:S94–105.
Hedges, L. V., W. Johnson, S. Semaan, and E. Sogolow. 2002. Theoretical issues in the synthesis of HIV prevention research. Journal of Acquired Immune Deficiency Syndromes 30:S8–14.
Neuman, M. S., W. D. Johnson, S. Semaan, S. A. Flores, G. Peersman, L. V. Hedges, and E. D. Sogolow. 2002. Review and meta-analysis of HIV prevention intervention research for heterosexual adult population in the United States. Journal of Acquired Immune Deficiency Syndromes 30:S106-117.
Semaan, S., D. DesJarlais, E. Sogolow, W. Johnson, L. V. Hedges, G. Ramírez, S. Flores, L. V. Norman, M. Sweat, and R. Needle. 2002. A meta-analysis of the effect of HIV prevention programs on the sex behaviors of drug users in the United States. Journal of Acquired Immune Deficiency Syndromes 30:S73-93.
Johnson, W., L. V. Hedges, G. Ramírez, S. Seeman, L. Norman, E. Sogolow, M. Sweat, and M. Diaz, 2002. HIV prevention research for men who have sex with men: A systematic review and meta-analysis. Journal of Acquired Immune Deficiency Syndromes 30:S118–130.
Hedges, L. V., J. Gurevitch, and P. Curtis. 1999. The meta-analysis of response ratios in experimental ecology. Ecology 80:1150–56.