结合局部比较组、预测测量和丰富协变量:它们在非等效比较组设计中共同减少偏倚的效果如何?

IF 3.5 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Seth Brown, Mengli Song, T. Cook, M. Garet
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引用次数: 3

摘要

本研究检查了8个非等效对照组设计(necgd)的偏倚减少,这些设计是由(a)局部与非局部对照组的选择,以及是否使用(b)研究结果的预试测量和(c)一组丰富的其他协变量组合而成的。偏倚被估计为每个NECGD与经过仔细评估的具有相同干预、结果和估计的随机实验之间因果估计的差异。结果表明,偏倚通常随着NECGD设计元素的数量而下降,将所有三个元素结合起来足以消除偏倚,但不是必需的,并且这种结果模式在五个不同的复制因子中很大程度上是重复的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining a Local Comparison Group, a Pretest Measure, and Rich Covariates: How Well Do They Collectively Reduce Bias in Nonequivalent Comparison Group Designs?
This study examined bias reduction in the eight nonequivalent comparison group designs (NECGDs) that result from combining (a) choice of a local versus non-local comparison group, and analytic use or not of (b) a pretest measure of the study outcome and (c) a rich set of other covariates. Bias was estimated as the difference in causal estimate between each NECGD and a carefully appraised randomized experiment with the same intervention, outcome, and estimand. Results indicated that bias generally declined with the number of design elements in an NECGD, that combining all three sufficed to eliminate bias but was not necessary for it, and that this pattern of results was largely replicated across five different replication factors.
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来源期刊
American Educational Research Journal
American Educational Research Journal EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
8.70
自引率
0.00%
发文量
19
期刊介绍: The American Educational Research Journal (AERJ) is the flagship journal of the American Educational Research Association, featuring articles that advance the empirical, theoretical, and methodological understanding of education and learning. It publishes original peer-reviewed analyses that span the field of education research across all subfields and disciplines and all levels of analysis. It also encourages submissions across all levels of education throughout the life span and all forms of learning. AERJ welcomes submissions of the highest quality, reflecting a wide range of perspectives, topics, contexts, and methods, including interdisciplinary and multidisciplinary work.
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