评估复杂多地点计划有效性的元分析方法。

Q2 Social Sciences New Directions for Evaluation Pub Date : 2022-01-01 Epub Date: 2022-08-08 DOI:10.1002/ev.20508
Catherine M Crespi, Krystle P Cobian
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引用次数: 0

摘要

美国国立卫生研究院(NIH)发起了 "建设多元化基础设施"(BUILD)倡议,鼓励本科院校采用创新方法来提高生物医学研究的多元化程度,最终目标是实现由 NIH 资助的研究企业的多元化。BUILD 等计划涉及在多个地点设计和实施具有共同目标的项目。对此类计划的评估通常包括统计分析,结合各研究机构的数据来估计计划对特定结果的影响。元分析是一种统计技术,用于综合不同研究的效果估计值,以获得单一的总体效果估计值,并估计不同研究之间的异质性。然而,该方法尚未普遍应用于评估一项计划对多个不同地点的影响。在本章中,我们将利用 "BUILD 奖学金 "计划--该计划的一个组成部分--来展示如何应用荟萃分析法来综合来自多地点计划中不同地点的效果估计值。我们使用典型的 "单一阶段 "建模方法和元分析方法对三种学生结果进行了分析。我们展示了元分析方法如何提供有关计划对学生成果影响的更细致信息,从而帮助支持稳健的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A meta-analysis approach for evaluating the effectiveness of complex multisite programs.

The National Institutes of Health (NIH) created the Building Infrastructure Leading to Diversity (BUILD) initiative to incentivize undergraduate institutions to create innovative approaches to increasing diversity in biomedical research, with the ultimate goal of diversifying the NIH-funded research enterprise. Initiatives such as BUILD involve designing and implementing programs at multiple sites that share common objectives. Evaluation of initiatives like this often includes statistical analyses that combine data across sites to estimate the program's impact on particular outcomes. Meta-analysis is a statistical technique for combining effect estimates from different studies to obtain a single overall effect estimate and to estimate heterogeneity across studies. However, it has not been commonly applied to evaluate the impact of a program across multiple different sites. In this chapter, we use the BUILD Scholar program-one component of the broader initiative-to demonstrate the application of meta-analysis to combine effect estimates from different sites of a multisite initiative. We analyze three student outcomes using a typical "single-stage" modeling approach and a meta-analysis approach. We show how a meta-analysis approach can provide more nuanced information about program impacts on student outcomes and thus can help support a robust evaluation.

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来源期刊
New Directions for Evaluation
New Directions for Evaluation Social Sciences-Education
CiteScore
2.70
自引率
0.00%
发文量
36
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