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Estimating the Normal Mean and Variance Under A Publication Selection Model

  • Larry V. Hedges

Abstract

Maximum likelihood estimators of the mean and variance of a normal distribution are obtained under a publication selection model in which data are reported only when the hypothesis that the mean is 0 is rejected. An approximation to the asymptotic variance-covariance matrix for these estimators is given. Also discussed are the marginal distributions of the sample mean and variance under the selection model.

Keywords

Selection Model Marginal Distribution Maximum Likelihood Estimator American Statistical Association Relative Bias 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1989

Authors and Affiliations

  • Larry V. Hedges
    • 1
  1. 1.University of ChicagoUSA

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