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On small sample inference for common mean in heteroscedastic one-way model. (English) Zbl 1049.62121
Summary: We consider and compare several approximate methods for making small-sample statistical inference on the common mean in the heteroscedastic one-way random effects model. The topic of the paper was motivated by the problem of interlaboratory comparisons and is also known as the (traditional) common mean problem. It is also closely related to the problem of multicenter clinical trials and meta-analysis.
Based on our simulation study we suggest to use the approach proposed by M. G. Kenward and J. H. Roger [Biometrics 53, 983–997 (1997; Zbl 0890.62042)] as an optimal choice for construction of the interval estimates of the common mean in the heteroscedastic one-way model.

MSC:
62P10 Applications of statistics to biology and medical sciences; meta analysis
62F25 Parametric tolerance and confidence regions
62E15 Exact distribution theory in statistics
62J10 Analysis of variance and covariance (ANOVA)
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