In sample survey, the complex set of measuring operations entails many procedures to check the data quality. At any step of the research process, errors can involve some bias in the estimates. Joining with sampling errors, nonsampling errors (NSE) contribute to set up “total survey error”. NSE arise from the combination of elements which could potentially distort measurement procedure, even the most accurate one, so affecting research outcomes. Some scholars proposed several classifications of NSE based on different criteria. In this paper, we check the quality of a database drawn from a survey about the tourism demand in Sicily. In particular, three types of NSE are reviewed: list errors, nonresponse errors and measurement errors.

Nonsampling Errors in Data Quality Control

D'AGATA, ROSARIO GIUSEPPE;TOMASELLI, Venera
2013

Abstract

In sample survey, the complex set of measuring operations entails many procedures to check the data quality. At any step of the research process, errors can involve some bias in the estimates. Joining with sampling errors, nonsampling errors (NSE) contribute to set up “total survey error”. NSE arise from the combination of elements which could potentially distort measurement procedure, even the most accurate one, so affecting research outcomes. Some scholars proposed several classifications of NSE based on different criteria. In this paper, we check the quality of a database drawn from a survey about the tourism demand in Sicily. In particular, three types of NSE are reviewed: list errors, nonresponse errors and measurement errors.
978-00-771-6100-2
Data quality; Nonsampling errors; Nonresponse errors
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/68845
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