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Autor
Lehtonen Risto (University of Helsinki, Finland)
Tytuł
Comments on "Probability vs. Nonprobability Sampling: From the Birth of Survey Sampling to the Present Day" by Graham Kalton
Źródło
Statistics in Transition, 2023, vol. 24, nr 3, s. 27-30, bibliogr. 14 poz.
Słowa kluczowe
Badania ankietowe, Badanie Internetu, Badania statystyczne, Metodologia badań statystycznych
Questionnaire survey, Internet survey, Statistical surveys, Methodology of statistical surveys
Uwagi
summ.
Abstrakt
The country's data infrastructure forms the basis of official statistics and opens up for me an important perspective on Kalton's presentation. Both probability and nonprobability sampling and inference can benefit from statistical data infrastructures that contain a rich selection of micro-level covariates drawn from a variety of administrative and other registers. Perhaps the best options are in countries where population data from register sources and sample data are linked for combined micro-level databases. (fragment of text)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. Citro, C. F., (2014). From multiple modes for surveys to multiple data sources for estimates. Survey Methodology, 40(2), pp. 137-161.
  2. Dunne, J. and Zhang, L.-C., (2023). A system of population estimates compiled from administrative data only. Journal of the Royal Statistical Society Series A: Statistics in Society. https://doi.org/10.1093/jrsssa/qnad065.
  3. Kim, J.-K., Park, S., Chen, Y. and Wu, C., (2021). Combining non-probability and probability survey samples through mass imputation. Journal of the Royal Statistical Society Series A: Statistics in Society, 184, pp. 941-963.
  4. Lehtonen, R., Särndal, C.-E. and Veijanen, A., (2003). The effect of model choice in estimation for domains, including small domains. Survey Methodology, 29(1), pp. 33-44.
  5. Lehtonen, R., Särndal, C.-E. and Veijanen, A., (2005). Does the model matter? Comparing model-assisted and model-dependent estimators of class frequencies for domains. Statistics in Transition, 7(3), pp. 649-673.
  6. Quality Description: Labour force survey, Statistics Finland 2022, (2022). https://www.tilastokeskus.fi/til/tyti/2022/01/tyti_2022_01_2022-02-22_laa_001_en.html
  7. Rancourt, E., (2018). Admin-First as a statistical paradigm for Canadian official statistics: Meaning, challenges and opportunities. Proceedings of Statistics Canada Symposium 2018.
  8. United Nations Economic Commission for Europe, (2007). Register-based statistics in the Nordic countries: Review of best practices with focus on population and social statistics. United Nations, New York. https://digitallibrary.un.org/record/609979?ln=en
  9. UNECE, (2018). Guidelines on the use of registers and administrative data for population and housing censuses. United Nations, New York and Geneva. https://unece.org/guidelines-use-registers-and-administrative-data-populationand-housing-censuses-0
  10. Yang, S. and Kim, J. K., (2020). Statistical data integration in survey sampling: a review. Jpn J Stat Data Sci, 3, pp. 625-650.
  11. Zhang, L.-C., (2012). Topics of statistical theory for register-based statistics and data integration. Statistica Neerlandica, 66(1), pp. 41-63.
  12. Zhang, L.-C. and Haraldsen, G., (2022). Secure big data collection and processing: framework, means and opportunities. Journal of the Royal Statistical Society: Series A, Statistics in Society, (In Press).
  13. Wallgren, A. and Wallgren, B., (2014). Register-Based Statistics: Administrative Data for Statistical Purposes. Second edition. Wiley.
  14. Wu, C., (2022). Statistical inference with non-probability survey samples. Survey Methodology, 48(2), pp. 283-311.
Cytowane przez
Pokaż
ISSN
1234-7655
Język
eng
URI / DOI
http://dx.doi.org/10.59170/stattrans-2023-031
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