Influence Diagnostics in Regression with Complex Designs Through Conditional Bias
One of the a,rea~s of Statistics in ~ hich the influence a, nalysis has been ~ idely stu.died in the multiple linear regression model. Nevertheless, the influence diagnostics propo,sed in this context cannot be applied to regression in complex survey, under randomized inference, s.ince the i.i.d, ca...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2005 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/138368 |
| Acesso em linha: | https://hdl.handle.net/11441/138368 https://doi.org/10.1007/BF02595416 |
| Access Level: | acceso abierto |
| Palavra-chave: | Conditional bias Influential observation Design baaed regression Survey sampling |
| Resumo: | One of the a,rea~s of Statistics in ~ hich the influence a, nalysis has been ~ idely stu.died in the multiple linear regression model. Nevertheless, the influence diagnostics propo,sed in this context cannot be applied to regression in complex survey, under randomized inference, s.ince the i.i.d, ca.se does not incorporate any probability weighting or population structure, such as clust, ering~ stratification or measures of size i~,to the analysis. In this paper we introduce ~)me influence diagnostics in regression in complex survey, They are built on the condition.al bias concept (Moreno-R, ebollo el, a,l,, 1999). We emphasize the similarities an.d differences of the propo.sed measures with respect to the existing ones for the i.i,d, case. |
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