Design-based random permutation models with auxiliary information
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
|---|---|
| Data(s) |
29/10/2013
29/10/2013
2012
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| Resumo |
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. National Institutes of Health, USA [NIH-PHS-R01-HD36848, R01-HL071828-02, 5R01HL079483] National Institutes of Health, USA Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazil Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazil |
| Identificador |
STATISTICS, ABINGDON, v. 46, n. 5, supl. 1, Part 3, pp. 663-671, MAY, 2012 0233-1888 http://www.producao.usp.br/handle/BDPI/36325 10.1080/02331888.2010.545408 |
| Idioma(s) |
eng |
| Publicador |
TAYLOR & FRANCIS LTD ABINGDON |
| Relação |
STATISTICS |
| Direitos |
restrictedAccess Copyright TAYLOR & FRANCIS LTD |
| Palavras-Chave | #AUXILIARY VARIABLE #DESIGN-BASED INFERENCE #PREDICTION #FINITE SAMPLING #RANDOM PERMUTATION MODEL #SIMULTANEOUS PERMUTATION #SAMPLE SURVEYS #PREDICTION #STATISTICS & PROBABILITY |
| Tipo |
article original article publishedVersion |
