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<p>The Global Flourishing Study (GFS) is an international collaboration to develop a publicly accessible data resource to promote global research on human flourishing. These data include over 200,000 participants from 22 geographically and culturally diverse countries and one territory designed to be nationally representative of the adult population. The GFS is intended as a longitudinal panel study with recruitment and empanelment for Wave 1 occurring between April 2022 and December 2023. Future waves of data collection will invite participants to complete a survey annually. The annual survey covers a robust set of measures on well-being, health, social, economic, political, religious, spiritual, psychological and demographic variables. The current paper describes the sampling methodology and weighting approaches used to project the samples to be nationally representative. Details are provided on interviewer training and data collection, probability and non-probability samples, creating weights, design effects, and future data collection stages.</p>

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Survey sampling design in wave 1 of the Global Flourishing Study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月27日

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  • R. Noah Padgett,
  • Richard G. Cowden,
  • Manas Chattopadhyay,
  • Ying Han,
  • John Honohan,
  • Zacc Ritter,
  • Rajesh Srinivasan,
  • Byron R. Johnson,
  • Tyler J. VanderWeele

摘要

The Global Flourishing Study (GFS) is an international collaboration to develop a publicly accessible data resource to promote global research on human flourishing. These data include over 200,000 participants from 22 geographically and culturally diverse countries and one territory designed to be nationally representative of the adult population. The GFS is intended as a longitudinal panel study with recruitment and empanelment for Wave 1 occurring between April 2022 and December 2023. Future waves of data collection will invite participants to complete a survey annually. The annual survey covers a robust set of measures on well-being, health, social, economic, political, religious, spiritual, psychological and demographic variables. The current paper describes the sampling methodology and weighting approaches used to project the samples to be nationally representative. Details are provided on interviewer training and data collection, probability and non-probability samples, creating weights, design effects, and future data collection stages.