Design-based random permutation models with auxiliary information
UMass Chan AffiliationsDepartment of Medicine, Division of Preventive and Behavioral Medicine
random permutation model
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AbstractWe extend the random permutation model to obtain the best linear unbiased estimator of a finite population mean accounting for auxiliary variables under simple random sampling without replacement (SRS) or stratified SRS. The proposed method provides a systematic design-based justification for well-known results involving common estimators derived under minimal assumptions that do not require specification of a functional relationship between the response and the auxiliary variables.
SourceLi W, Stanek EJ 3rd, Singer JM. Design-based random permutation models with auxiliary information(¶). Statistics (Ber). 2012 Jan 1;46(5):663-671. Link to article on publisher's site
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/44864
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