Estimation of Population Mean in the Presence of Non-Response and Measurement Error

• SUNIL KUMAR ^[1] ; SANDEEP BHOUGAL ^[2] ; N. S. NATARAJA ^[1] ; M. VISWANATHAIAH ^[1]
  1. [1] Alliance University

     Alliance University

     India

     
  2. [2] Shri Mata Vaishno Devi University School of Mathematics
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 38, Nº. 1, 2015, págs. 145-161
• Idioma: inglés
• DOI: 10.15446/rce.v38n1.48807
• Títulos paralelos:
  • Estimacion de la media poblacional con presencia de errores de medición y no respuesta
• Enlaces
  • Texto completo
• Resumen
  • español

    En la teoría de muestreo de la encuesta clásica los errores estudiados principalmente en la estimación son el muestreo errores. Sin embargo, a menudo los errores ajenos al muestreo son más influyentes que las propiedades del estimador de errores de muestreo. Esto es reconocido por los profesionales, los investigadores y muchos grandes obras de la literatura en relación con los errores ajenos al muestreo se ha publicado en los últimos dos decenios, especialmente en relación con el error de falta de respuesta, que es una de las piedras angulares de los errores ajenos al muestreo. La literatura se ocupa de un tipo de error no muestral a la vez, aunque en las encuestas reales más de un error no muestral suele estar presente. En este trabajo, dos tipos de errores ajenos al muestreo son considerados en la etapa de la estimación: la falta de respuesta y el error de medición. Un tipo exponencial estimador de razón ha sido desarrollado para estimar la media poblacional de la variable de respuesta en presencia de errores de falta de respuesta y de medición. Teóricamente y empíricamente, se ha mostrado que el estimador propuesto es más eficiente que estimador insesgado habitual y otros estimadores existentes.

  • English

    Under classical survey sampling theory the errors mainly studied in the estimation are sampling errors. However, often non-sampling errors are more influential to the properties of the estimator than sampling errors. This is recognized by practitioners, researchers and many great works of literature regarding non-sampling errors have been published during last two decades, especially regarding non-response error which is one of the cornerstones of the non-sampling errors. The literature handles one kind of non-sampling error at a time, although in real surveys more than one non-sampling error is usually present.In this paper, two kinds of non-sampling errors are considered at the estimation stage: non-response and measurement error. An exponential ratio type estimator has been developed to estimate the population mean of the response variable in the presence of non-response and measurement errors. Theoretically and empirically, it has been shown that the proposed estimator is more efficient than usual unbiased estimator and other existing estimators.

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