元分析的四个最佳实践:对残疾学生或有残疾风险学生数学干预方法论严谨性的系统评价

IF 1.6 4区 教育学 Q2 EDUCATION, SPECIAL
Soyoung Park, Young Ri Lee, Gena Nelson, Elizabeth Tipton
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引用次数: 0

摘要

随着更稳健的统计技术的发展,元分析方法也在不断发展;然而,很少有关于特殊教育的评论特别关注荟萃分析方法的严谨性。在这项研究中,我们检查了2000年至2022年发表的29项数学干预元分析,以确定研究人员在关注残疾学生数学干预的元分析中应用四种最佳实践的程度。我们的发现是:(a)研究使用了三种主要的调节技术:元回归(k = 10)、亚组分析(k = 8)、方差分析(k = 3)以及亚组分析和元回归(k = 1);(b)只有一项研究考虑了假设检验的小样本修正;(c)很少有研究者处理多个效应量之间的相关性(k = 3);(d)漏斗图通常用于检测发表偏倚(k = 8)。根据我们的发现,我们对未来meta分析的方法学考虑提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Four Best Practices for Meta-Analysis: A Systematic Review of Methodological Rigor in Mathematics Interventions for Students With or at Risk of Disabilities
Meta-analysis methodology has evolved with the development of more robust statistical techniques; however, few reviews in special education have focused specifically on methodological rigor in meta-analyses. In this study, we examined 29 meta-analyses of mathematics interventions published from 2000 to 2022 to determine the extent to which researchers have applied four best practices in meta-analyses focused on mathematics interventions for students with disabilities. Our findings were (a) studies used three primary moderator techniques: meta-regression ( k = 10), subgroup analysis ( k = 8), analysis of variance ( k = 3), and both subgroup analysis and meta-regression ( k = 1); (b) only one study considered small sample corrections for hypothesis tests; (c) few researchers handled the dependence between multiple effect sizes ( k = 3); and (d) the funnel plot was commonly used to detect publication bias ( k = 8). Based on our findings, we make recommendations for methodological considerations for future meta-analyses.
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来源期刊
CiteScore
3.50
自引率
11.10%
发文量
19
期刊介绍: Learning Disability Quarterly publishes high-quality research and scholarship concerning children, youth, and adults with learning disabilities. Consistent with that purpose, the journal seeks to publish articles with the potential to impact and improve educational outcomes, opportunities, and services.
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