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<p>This study explores the use of Small Area Estimation (SAE) methods to expand reporting of state-level subgroup performance on National Assessment of Educational Progress (NAEP) assessments without requiring the assessment program to draw larger samples of students and expand test administration. To evaluate the SAE methods, small area estimates of mean subgroup achievement formed from samples too small to meet NAEP’s current reporting requirements are compared with design-based estimates of mean subgroup achievement that satisfy the program’s minimum sample size requirement for reporting. Results demonstrate that several SAE methods yield estimates of mean achievement that are more accurate and reliable than estimates of mean achievement that satisfy NAEP’s current reporting requirement. Policy implications and future directions for research are discussed.</p>

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An appraisal of small area estimation methods to explore expansion of state subgroup reporting on NAEP

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月22日

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  • David Bamat,
  • Sinan Yavuz,
  • Paulina Grekov

摘要

This study explores the use of Small Area Estimation (SAE) methods to expand reporting of state-level subgroup performance on National Assessment of Educational Progress (NAEP) assessments without requiring the assessment program to draw larger samples of students and expand test administration. To evaluate the SAE methods, small area estimates of mean subgroup achievement formed from samples too small to meet NAEP’s current reporting requirements are compared with design-based estimates of mean subgroup achievement that satisfy the program’s minimum sample size requirement for reporting. Results demonstrate that several SAE methods yield estimates of mean achievement that are more accurate and reliable than estimates of mean achievement that satisfy NAEP’s current reporting requirement. Policy implications and future directions for research are discussed.