Influence Diagnostics in Regression with Complex Designs Through Conditional Bias

• Autores: Ana María Muñoz Reyes , Juan Manuel Muñoz Pichardo , Juan Luis Moreno Rebollo
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 14, Nº. 2, 2005, págs. 515-542
• Idioma: inglés
• DOI: 10.1007/bf02595416
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• Resumen

  • One of the areas of Statistics in which the influence analysis has been widely studied is the multiple linear regression model. Nevertheless, the influence diagnostics proposed in this context cannot be applied to regression in complex survey, under randomized inference, since the i.i.d. case does not incorporate any probability weighting or population structure, such as clustering, stratification or measures of size into the analysis. In this paper we introduce some influence diagnostics in regression in complex survey. They are built on the conditional bias concept(Moreno-Rebollo et al., 1999). We emphasize the similarities and differences of the proposed measures with respect to the existing ones for the i.i.d. case.