Linearly admissible estimators of mean vector with respect to balanced loss function in multivariate statistics |
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Authors: | Ming-Xiang Cao Guang-Jun Shena |
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Institution: | 1. School of Mathematics and Computer Science, Anhui Normal University, Wuhu 241000, P. R. China;2. Department of Mathematics, Hefei Normal University, Hefei 230601, P. R. Chinacaomingx@163.com |
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Abstract: | The authors discuss the bias of the estimate of the variance of the overall effect synthesized from individual studies by using the variance weighted method. This bias is proven to be negative. Furthermore, the conditions, the likelihood of underestimation and the bias from this conventional estimate are studied based on the assumption that the estimates of the effect are subject to normal distribution with common mean. The likelihood of underestimation is very high (e.g. it is greater than 85% when the sample sizes in two combined studies are less than 120). The alternative less biased estimates for the cases with and without the homogeneity of the variances are given in order to adjust for the sample size and the variation of the population variance. In addition, the sample size weight method is suggested if the consistence of the sample variances is violated Finally, a real example is presented to show the difference by using the above three estimate methods. |
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Keywords: | Admissibility Balanced loss function Linear estimators Mean vector Multivariate statistics |
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