Design-based random permutation models with auxiliary information
UMass Chan Affiliations
Department of Medicine, Division of Preventive and Behavioral MedicineDocument Type
Journal ArticlePublication Date
2012-01-01Keywords
auxiliary variabledesign-based inference
prediction
finite sampling
random permutation model
simultaneous permutation
Statistical Models
Metadata
Show full item recordAbstract
We 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.Source
Li 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 siteDOI
10.1080/02331888.2010.545408Permanent Link to this Item
http://hdl.handle.net/20.500.14038/44864PubMed ID
23645951Related Resources
Link to Article in PubMedae974a485f413a2113503eed53cd6c53
10.1080/02331888.2010.545408