Properties of the weighting cell estimator under a nonparametric response mechanism
The weighting cell estimator corrects for unit nonresponse by dividing the sample into homogeneous groups (cells) and applying a ratio correction to the respondents within each cell. Previous studies of the statistical properties of weighting cell estimators have assumed that these cells correspon...
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| Principais autores: | , |
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| Formato: | article |
| Idioma: | eng |
| Publicado em: |
Survey Methodology
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/26222 |
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| Resumo: | The weighting cell estimator corrects for unit nonresponse by dividing the sample into homogeneous groups (cells) and
applying a ratio correction to the respondents within each cell. Previous studies of the statistical properties of weighting cell
estimators have assumed that these cells correspond to known population cells with homogeneous characteristics. In this
article, we study the properties of the weighting cell estimator under a response probability model that does not require
correct specification of homogeneous population cells. Instead, we assume that the response probabilities are a smooth but
otherwise unspecified function of a known auxiliary variable. Under this more general model, we study the robustness of the
weighting cell estimator against model misspecification. We show that, even when the population cells are unknown, the
estimator is consistent with respect to the sampling design and the response model. We describe the effect of the number of
weighting cells on the asymptotic properties of the estimator. Simulation experiments explore the finite sample properties of
the estimator. We conclude with some guidance on how to select the size and number of cells for practical implementation
of weighting cell estimation when those cells cannot be specified a priori. |
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