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https://doi.org/10.1007/978-3-030-47515-4_11

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Linking PIAAC Data to Individual Administrative Data: Insights from a German Pilot Project

[collection article]


This document is a part of the following document:
Large-Scale Cognitive Assessment: Analyzing PIAAC Data

Daikeler, Jessica
Gauly, Britta
Rosenthal, Matthias

Abstract

Linking survey data to administrative data offers researchers many opportunities. In particular, it enables them to enrich survey data with additional information without increasing the burden on respondents. German PIAAC data on individual skills, for example, can be combined with administrative da... view more

Linking survey data to administrative data offers researchers many opportunities. In particular, it enables them to enrich survey data with additional information without increasing the burden on respondents. German PIAAC data on individual skills, for example, can be combined with administrative data on individual employment histories. However, as the linkage of survey data with administrative data records requires the consent of respondents, there may be bias in the linked dataset if only a subsample of respondents - for example, high-educated individuals - give their consent. The present chapter provides an overview of the pilot project about linking the German PIAAC data with individual administrative data. In a first step, we illustrate characteristics of the linkable datasets and describe the linkage process and its methodological challenges. In a second step, we provide an illustrative example of the use of the linked data and investigate how the skills assessed in PIAAC are associated with the linkage decision.... view less

Keywords
survey research; data capture; data preparation; data quality

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
PIAAC; PIAAC-L; administrative data; data linkage; consent to linkage

Collection Title
Large-Scale Cognitive Assessment: Analyzing PIAAC Data

Editor
Maehler, Débora B.; Rammstedt, Beatrice

Document language
English

Publication Year
2020

Publisher
Springer

City
Cham

Page/Pages
p. 271-290

Series
Methodology of Educational Measurement and Assessment

ISSN
2367-1718

ISBN
978-3-030-47515-4

Status
Published Version; reviewed

Licence
Creative Commons - Attribution 4.0


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.