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Clustering estimates of effect magnitude from independent studies
Larry V. Hedges
*
, Ingram Olkin
*
Corresponding author for this work
Statistics and Data Science
Research output
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Article
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peer-review
29
Scopus citations
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Dive into the research topics of 'Clustering estimates of effect magnitude from independent studies'. Together they form a unique fingerprint.
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Keyphrases
Cluster Studies
20%
Common Effects
20%
Correlation Coefficient
40%
Disjoint
20%
Effect Magnitude
100%
Homogeneity Test
20%
Overlapping Clusters
20%
Parameter Correlation
20%
Size Parameter
20%
Standardized Mean Difference
60%
Statistical Significance Levels
20%
Mathematics
Common Effect
50%
correlation coefficient ρ
100%
Effect Size
50%
significance level α
100%
Statistical Significance
50%
Engineering
Effect Size
50%
Significance Level
100%
Size Parameter
50%
Computer Science
Significance Level
100%
Size Parameter
50%
Economics, Econometrics and Finance
Correlation Coefficient
100%
Psychology
Standardized Mean Difference
100%