Mapping the evolution of sampling design in large-scale surveys: A comprehensive systematic analysis of global trends, methodological dynamics, and journal impact in survey research and data science
Main Article Content
Abstract
An accurate and efficient sampling design plays a vital role in ensuring the reliability, validity, and representativeness of data collected through large-scale surveys. As survey research and data science have developed, the ways of planning and carrying out sampling have steadily evolved to keep up with new challenges and technologies. This study presents a comprehensive systematic analysis of the evolution of sampling design, exploring global trends, methodological developments, and thematic progressions within this essential field. Drawing on 262 publications published between 1979 and 2024, the research maps the trajectory of scholarly contributions, highlighting both established and emerging areas of interest. The analysis of country contributions demonstrates long-standing leadership from particular high-output nations, as well as increased engagement from developing countries. Thematic findings highlight a consistent increase in scholarly output over recent decades, with a focus on methodological issues such as variance estimates, sampling weights, and probabilistic design techniques. Network, factorial, and trend studies demonstrate these concepts' interconnection and changing importance within the subject. This study not only synthesizes decades of academic discourse but also underscores the need for continuous methodological refinement to address the complexities of modern data environments. The findings offer valuable direction for future research and contribute to strengthening the foundations of survey methodology.
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