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Adaptive Survey Design for the Dutch Labour Force Survey

Received: 19 July 2022     Accepted: 23 August 2022     Published: 31 August 2022
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Abstract

A challenge for the National Statistical Institutes is to produce reliable statistics with a limited budget for data collection. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done on the impact on quality and costs of reducing the use of interviewers in mixed-mode surveys that start with Internet observation, followed by telephone or face-to-face observation of Internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. For this purpose, a methodology has been developed in this paper. The methodology is applied in the development of an adaptive survey design for the Dutch Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and some response and survey results.

Published in American Journal of Theoretical and Applied Statistics (Volume 11, Issue 4)
DOI 10.11648/j.ajtas.20221104.12
Page(s) 114-121
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Balanced Response, Nonresponse Bias, Accuracy, Data Collection

References
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Cite This Article
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    Kees van Berkel. (2022). Adaptive Survey Design for the Dutch Labour Force Survey. American Journal of Theoretical and Applied Statistics, 11(4), 114-121. https://doi.org/10.11648/j.ajtas.20221104.12

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    Kees van Berkel. Adaptive Survey Design for the Dutch Labour Force Survey. Am. J. Theor. Appl. Stat. 2022, 11(4), 114-121. doi: 10.11648/j.ajtas.20221104.12

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    AMA Style

    Kees van Berkel. Adaptive Survey Design for the Dutch Labour Force Survey. Am J Theor Appl Stat. 2022;11(4):114-121. doi: 10.11648/j.ajtas.20221104.12

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  • @article{10.11648/j.ajtas.20221104.12,
      author = {Kees van Berkel},
      title = {Adaptive Survey Design for the Dutch Labour Force Survey},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {11},
      number = {4},
      pages = {114-121},
      doi = {10.11648/j.ajtas.20221104.12},
      url = {https://doi.org/10.11648/j.ajtas.20221104.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20221104.12},
      abstract = {A challenge for the National Statistical Institutes is to produce reliable statistics with a limited budget for data collection. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done on the impact on quality and costs of reducing the use of interviewers in mixed-mode surveys that start with Internet observation, followed by telephone or face-to-face observation of Internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. For this purpose, a methodology has been developed in this paper. The methodology is applied in the development of an adaptive survey design for the Dutch Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and some response and survey results.},
     year = {2022}
    }
    

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    AB  - A challenge for the National Statistical Institutes is to produce reliable statistics with a limited budget for data collection. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done on the impact on quality and costs of reducing the use of interviewers in mixed-mode surveys that start with Internet observation, followed by telephone or face-to-face observation of Internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. For this purpose, a methodology has been developed in this paper. The methodology is applied in the development of an adaptive survey design for the Dutch Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and some response and survey results.
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Author Information
  • Statistics Netherlands, Division of Data Services, Research and Innovation, Heerlen, the Netherlands

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