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  • 标题:Examining Design and Statistical Power for Planning Cluster Randomized Trials Aimed at Improving Student Science Achievement and Science Teacher Outcomes
  • 本地全文:下载
  • 作者:Qi Zhang ; Jessaca Spybrook ; Fatih Unlu
  • 期刊名称:AERA Open
  • 印刷版ISSN:2332-8584
  • 电子版ISSN:2332-8584
  • 出版年度:2020
  • 卷号:6
  • 期号:3
  • 页码:1-12
  • DOI:10.1177/2332858420939526
  • 摘要:With the increasing demand for evidence-based research on teacher effectiveness and improving student achievement, more impact studies are being conducted to examine the effectiveness of professional development (PD) interventions. Cluster randomized trials (CRTs) are often carried out to assess PD interventions that aim to improve both teacher and student outcomes. Due to the different design parameters (i.e., intraclass correlation and R 2 ) and benchmark effect sizes associated with the student and teacher outcomes, two power analyses are necessary for planning CRTs that aim to detect both teacher and student effects in one study. These two power analyses are often conducted separately without considering how design choices to power the study to detect student effects may affect design choices to power the study to detect teacher effects and vice versa. In this study, we consider strategies to maximize the efficiency of the study design when both student and teacher effects are of primary interest.
  • 关键词:study design; power analysis; cluster randomized trial; science education
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