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N. Jacobson, P. Truax (1991)
Clinical significance: a statistical approach to defining meaningful change in psychotherapy research.Journal of consulting and clinical psychology, 59 1
L. Hedges (1982)
Estimation of effect size from a series of independent experiments.Psychological Bulletin, 92
(2001)
Publication Manual of the American Psychological Association
R. Rosenthal, R. Rosnow (1984)
Essentials of Behavioral Research: Methods and Data Analysis
L.V. Hedges (1981)
Distribution theory for Glass's estimator of effect size and related measuresJournal of Educational Statistics, 6
J. Cohen (1987)
Statistical Power Analysis for Behavioral Sciences
R. Gibbons, D. Hedeker, J. Davis (1993)
Estimation of Effect Size From a Series of Experiments Involving Paired ComparisonsJournal of Educational Statistics, 18
Frank Wolf, Donald Owen (1962)
Handbook of Statistical Tables.Biometrika, 50
G. Glass, B. Mcgaw, M. Smith (1981)
Meta-analysis in social research
L. Hedges (1981)
Distribution Theory for Glass's Estimator of Effect size and Related EstimatorsJournal of Educational Statistics, 6
R. Kirk (1996)
Practical Significance: A Concept Whose Time Has ComeEducational and Psychological Measurement, 56
L. Hedges, I. Olkin (1987)
Statistical Methods for Meta-Analysis
S. Morris, R. DeShon (2002)
Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs.Psychological methods, 7 1
W. Dunlap, J. Cortina, Joel Vaslow, M. Burke (1996)
Meta-Analysis of Experiments With Matched Groups or Repeated Measures DesignsPsychological Methods, 1
H. Friedman (1968)
Magnitude of experimental effect and a table for its rapid estimation.Psychological Bulletin, 70
S. Morris (2000)
Distribution of the standardized mean change effect size for meta-analysis on repeated measures.The British journal of mathematical and statistical psychology, 53 ( Pt 1)
R. Rosnow, R. Rosenthal (1996)
Computing Contrasts, Effect Sizes, and Counternulls on Other People's Published Data: General Procedures for Research ConsumersPsychological Methods, 1
Effect Sizes (ES) are an increasingly important index used toquantify the degree of practical significanceof study results. This paper gives anintroduction to the computation andinterpretation of effect sizes from theperspective of the consumer of the researchliterature. The key points made are:1. ES is a useful indicator of the practical(clinical) importance of research resultsthat can be operationally defined frombeing ``negligible'' to ``moderate'', to``important''.2. The ES has two advantages overstatistical significance testing: (a) itis independent of the size of the sample;(b) it is a scale-free index. Therefore,ES can be uniformly interpreted indifferent studies regardless of the samplesize and the original scales of thevariables.3. Calculations of the ES are illustrated byusing examples of comparisons between twomeans, correlation coefficients,chi-square tests and two proportions,along with appropriate formulas.4. Operational definitions for the ESs aregiven, along with numerical examples forthe purpose of illustration.
Advances in Health Sciences Education – Springer Journals
Published: Sep 21, 2004
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