Estimating the Normal Mean and Variance Under A Publication Selection Model
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.
KeywordsSelection Model Marginal Distribution Maximum Likelihood Estimator American Statistical Association Relative Bias
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