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231226s2022 xx |||||o 00| ||eng c |
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|a 10.1002/ev.20508
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|a eng
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1 |
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|a Crespi, Catherine M
|e verfasserin
|4 aut
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|a A meta-analysis approach for evaluating the effectiveness of complex multisite programs
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|c 2022
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 23.01.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a 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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|a Journal Article
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|a Cobian, Krystle P
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t New directions for evaluation
|d 1999
|g 2022(2022), 174 vom: 12., Seite 47-56
|w (DE-627)NLM098252755
|x 1097-6736
|7 nnas
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| 773 |
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|g volume:2022
|g year:2022
|g number:174
|g day:12
|g pages:47-56
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|u http://dx.doi.org/10.1002/ev.20508
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|d 2022
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