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Hedges, Larry V.; Schauer, Jacob M. – Grantee Submission, 2019
Formal empirical assessments of replication have recently become more prominent in several areas of science, including psychology. These assessments have used different statistical approaches to determine if a finding has been replicated. The purpose of this article is to provide several alternative conceptual frameworks that lead to different…
Descriptors: Statistical Analysis, Replication (Evaluation), Meta Analysis, Hypothesis Testing
Borenstein, Michael; Higgins, Julian P. T.; Hedges, Larry V.; Rothstein, Hannah R. – Research Synthesis Methods, 2017
When we speak about heterogeneity in a meta-analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention yields a mean effect size of 50 points, we want to know if the effect size in different populations varies from 40 to 60, or from 10 to 90, because this speaks to the potential utility of…
Descriptors: Meta Analysis, Effect Size, Intervention, Prediction
Pustejovsky, James E.; Hedges, Larry V.; Shadish, William R. – Journal of Educational and Behavioral Statistics, 2014
In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…
Descriptors: Hierarchical Linear Modeling, Effect Size, Maximum Likelihood Statistics, Computation
Hedges, Larry V.; Pustejovsky, James E.; Shadish, William R. – Online Submission, 2012
Single case designs are a set of research methods for evaluating treatment effects by assigning different treatments to the same individual and measuring outcomes over time and are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single case designs have focused attention on…
Descriptors: Research Design, Effect Size, Meta Analysis, Computation

Hedges, Larry V. – New Directions for Program Evaluation, 1984
The adequacy of traditional effect size measures for research synthesis is challenged. Analogues to analysis of variance and multiple regression analysis for effect sizes are presented. The importance of tests for the consistency of effect sizes in interpreting results, and problems in obtaining well-specified models for meta-analysis are…
Descriptors: Analysis of Variance, Effect Size, Mathematical Models, Meta Analysis
Hedges, Larry V.; Pigott, Therese D. – Psychological Methods, 2004
Calculation of the statistical power of statistical tests is important in planning and interpreting the results of research studies, including meta-analyses. It is particularly important in moderator analyses in meta-analysis, which are often used as sensitivity analyses to rule out moderator effects but also may have low statistical power. This…
Descriptors: Goodness of Fit, Multiple Regression Analysis, Effect Size, Statistical Analysis
Hedges, Larry V.; And Others – 1989
Methods for meta-analysis have evolved dramatically since Gene Glass first proposed the term in 1976. Since that time statistical and nonstatistical aspects of methodology for meta-analysis have been developing at a steady pace. This guide is an attempt to provide a practical introduction to rigorous procedures in the meta-analysis of social…
Descriptors: Comparative Analysis, Effect Size, Higher Education, Meta Analysis

Hedges, Larry V.; And Others – Educational Researcher, 1994
Replies to E. A. Hanushek's questioning of the validity of meta-analysis as used by the authors in analyzing resource allocation and its effects on improving student academic performance. Statistical analysis procedures are examined. (GLR)
Descriptors: Academic Achievement, Criticism, Educational Facilities Improvement, Educational Policy

Hedges, Larry V.; And Others – Educational Researcher, 1994
Presents reanalysis of data from earlier reviews, particularly those by Hanushek (1981, 1986, 1989, 1991), on relationship between educational resource input and school outcomes when controlling for student characteristics such as socioeconomic status. Using different synthesis methods, analysis shows a positive relationship between resources and…
Descriptors: Academic Achievement, Educational Facilities, Educational Resources, Elementary Secondary Education