Arbeitspapier

The Data Quality Concept of Accuracy in the Context of Public Use Data Sets

Like other data quality dimensions, the concept of accuracy is often adopted to characterise a particular data set. However, its common specification basically refers to statistical properties of estimators, which can hardly be proved by means of a single survey at hand. This ambiguity can be resolved by assigning ?accuracy? to survey processes that are known to affect these properties. In this contribution, we consider the sub-process of imputation as one important step in setting up a data set and argue that the so called ?hit-rate? criterion, that is intended to measure the accuracy of a data set by some distance function of ?true? but unobserved and imputed values, is neither required nor desirable. In contrast, the so-called ?inference? criterion allows for valid inferences based on a suitably completed data set under rather general conditions. The underlying theoretical concepts are illustrated by means of a simulation study. It is emphasised that the same principal arguments apply to other survey processes that introduce uncertainty into an edited data set.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 586

Classification
Wirtschaft
Statistical Simulation Methods: General
Estimation: General
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Bayesian Analysis: General
Classification Discontinued 2008. See C83.
Subject
Survey Quality
Survey Processes
Accuracy
Assessment of Imputation Methods
Multiple Imputation

Event
Geistige Schöpfung
(who)
Kuchler, Carsten
Spiess, Martin
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2006

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Kuchler, Carsten
  • Spiess, Martin
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

  • 2006

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