Small-area estimation using adjustment by covariantes.

Nicholas T. Longford

Qüestiió (1996)

  • Volume: 20, Issue: 2, page 187-212
  • ISSN: 0210-8054

Abstract

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Linear regression models with random effects are applied to estimating the population means of indirectly measured variables in small areas. The proposed method, a hybrid with design- and model-based elements, takes account of the area-level variation and of the uncertainty about the fitted regression model and the area-level population means of the covariates. The method is illustrated on data from the U.S. Department of Labor Literacy Surveys and is informally validated on two states, Mississippi and Oregon, for which statewide surveys have been conducted.

How to cite

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Longford, Nicholas T.. "Small-area estimation using adjustment by covariantes.." Qüestiió 20.2 (1996): 187-212. <http://eudml.org/doc/40214>.

@article{Longford1996,
abstract = {Linear regression models with random effects are applied to estimating the population means of indirectly measured variables in small areas. The proposed method, a hybrid with design- and model-based elements, takes account of the area-level variation and of the uncertainty about the fitted regression model and the area-level population means of the covariates. The method is illustrated on data from the U.S. Department of Labor Literacy Surveys and is informally validated on two states, Mississippi and Oregon, for which statewide surveys have been conducted.},
author = {Longford, Nicholas T.},
journal = {Qüestiió},
keywords = {Regresión lineal; Tamaño muestral; Media poblacional; effective sample; size; linear regression; random effect; sampling variation},
language = {eng},
number = {2},
pages = {187-212},
title = {Small-area estimation using adjustment by covariantes.},
url = {http://eudml.org/doc/40214},
volume = {20},
year = {1996},
}

TY - JOUR
AU - Longford, Nicholas T.
TI - Small-area estimation using adjustment by covariantes.
JO - Qüestiió
PY - 1996
VL - 20
IS - 2
SP - 187
EP - 212
AB - Linear regression models with random effects are applied to estimating the population means of indirectly measured variables in small areas. The proposed method, a hybrid with design- and model-based elements, takes account of the area-level variation and of the uncertainty about the fitted regression model and the area-level population means of the covariates. The method is illustrated on data from the U.S. Department of Labor Literacy Surveys and is informally validated on two states, Mississippi and Oregon, for which statewide surveys have been conducted.
LA - eng
KW - Regresión lineal; Tamaño muestral; Media poblacional; effective sample; size; linear regression; random effect; sampling variation
UR - http://eudml.org/doc/40214
ER -

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