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<p>In this article, we describe the statistical and design methodology of the demographic variation analyses used as part of a coordinated set of manuscripts for wave 1 of the Global Flourishing Study (GFS). Aspects covered include the following: childhood predictors regression analyses, accounting for the complex sampling design, missing data and imputation, sensitivity analysis for unmeasured confounding and meta-analysis. We provide a brief illustrative example of the childhood predictor analyses using the sense of mastery construct indicator from the GFS survey and conclude by outlining some strengths and limitations of the methodology employed.</p>

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Analytic methodology for childhood predictor analyses for wave 1 of the Global Flourishing Study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月30日

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  • R. Noah Padgett,
  • Matt Bradshaw,
  • Ying Chen,
  • Richard G. Cowden,
  • Sung Joon Jang,
  • Eric S. Kim,
  • Koichiro Shiba,
  • Byron R. Johnson,
  • Tyler J. VanderWeele

摘要

In this article, we describe the statistical and design methodology of the demographic variation analyses used as part of a coordinated set of manuscripts for wave 1 of the Global Flourishing Study (GFS). Aspects covered include the following: childhood predictors regression analyses, accounting for the complex sampling design, missing data and imputation, sensitivity analysis for unmeasured confounding and meta-analysis. We provide a brief illustrative example of the childhood predictor analyses using the sense of mastery construct indicator from the GFS survey and conclude by outlining some strengths and limitations of the methodology employed.