Simultaneous Inference on All Linear Combinations of Means with Heteroscedastic Errors
Author(s) -
Xin Yan,
Xiaogang Su
Publication year - 2011
Publication title -
journal of probability and statistics
Language(s) - English
Resource type - Journals
eISSN - 1687-9538
pISSN - 1687-952X
DOI - 10.1155/2011/484272
Subject(s) - heteroscedasticity , mathematics , pairwise comparison , confidence interval , statistics , inference , variance (accounting) , multiple comparisons problem , linear model , confidence region , computer science , artificial intelligence , accounting , business
We proposed a statistical method to construct simultaneous confidence intervals on all linear combinations of means without assuming equal variance where the classical Scheffé's simultaneous confidence intervals no longer preserve the familywise error rate (FWER). The proposed method is useful when the number of comparisons on linear combinations of means is extremely large. The FWERs for proposed simultaneous confidence intervals under various configurations of mean variances are assessed through simulations and are found to preserve the predefined nominal level very well. An example of pairwise comparisons on heteroscedastic means is given to illustrate the proposed method
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