Survey Methodology
Comments by M. Giovanna RanalliNote 1 on “Trends and directions in sample survey theory and methods”

  • Release date: June 30, 2025
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Abstract

This discussion examines some advancements in survey design and estimation, inspired by the comprehensive appraisal of Professors Jon Rao and Sharon Lohr on current trends in the field. It delves into three specific areas: balanced sampling, calibration, and small area estimation. Probabilistic balanced sampling methods, such as the cube method and penalized balanced sampling, are explored, with an emphasis on addressing emerging challenges, including extensions to linear mixed models, nonparametric regression models, and spatially balanced designs. Calibration is discussed using a modular framework that incorporates modern regression techniques, and highlights innovative uses of model calibration for data editing and causal inference. Small area estimation is considered in the context of latent variable modeling and data integration, emphasizing its role when the variable(s) of interest cannot be measured either directly or without error. Applications in integrating probability and non-probability data and conducting causal analysis at local level are also discussed.

Key Words:    Balanced sampling; Causal inference; Data integration; Latent variable models; Model calibration; Small area estimation.

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How to cite

Ranalli, M.G. (2025). Comments on “Trends and directions in sample survey theory and methods”. Survey Methodology, 51(1), 131-139. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2025001/article/00011-eng.pdf.

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ISSN : 1492-0921

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Survey Methodology publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in Survey Methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves. All papers will be refereed. However, the authors retain full responsibility for the contents of their papers and opinions expressed are not necessarily those of the Editorial Board or of Statistics Canada.

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© His Majesty the King in Right of Canada, as represented by the Minister of Industry, 2025

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Catalogue No. 12-001-X

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