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Hedges, Larry V. – Journal of Educational Statistics, 1984
If the quantitative result of a study is observed only when the mean difference is statistically significant, the observed mean difference, variance, and effect size are biased estimators of corresponding population parameters. The exact distribution of sample effect size and the maximum likelihood estimator of effect size are derived. (Author/BW)
Descriptors: Effect Size, Estimation (Mathematics), Maximum Likelihood Statistics, Meta Analysis

Orwin, Robert G. – Journal of Educational Statistics, 1983
Rosenthan's (1979) concept of fail-safe N has thus far been applied to probability levels exclusively. This note introduces a fail-safe N for effect size. (Author)
Descriptors: Effect Size, Meta Analysis, Research Design, Research Problems

Ross, Kenneth N. – Journal of Educational Statistics, 1979
It is shown that using formulae for the estimation of sampling errors based on simple random sampling, when a design actually involves cluster sampling, can lead to serious underestimation of error. Jackknife and balanced repeated replication are recommended as techniques for dealing with this problem. (Author/CTM)
Descriptors: Foreign Countries, Hypothesis Testing, Research Design, Research Problems