Estimating a Dose-Response Relationship in Quasi-Experimental Student Success Studies
Estimating a Dose-Response Relationship in Quasi-Experimental Student Success Studies
复制标题
估计准实验学生成功研究中的剂量反应关系
DOI:
10.1007/s40593-021-00280-0
复制
发表时间:
2022
影响因子:
4.9
通讯作者:
Fan, Juanjuan
中科院分区:
文献类型:
--
作者:
Shao, Lucy;Levine, Richard A.;Guarcello, Maureen A.;Wilke, Morten C.;Stronach, Jeanne;Frazee, James P.;Fan, Juanjuan
Propensity score matching and weighting methods are applied to balance covariates and reduce selection bias in the analysis of observational study data, and ultimately estimate a treatment effect. We wish to evaluate the impact of a Supplemental Instruction (SI) program on student success in an Introductory Statistics course. In such student success studies, propensity score methods have been applied successfully for evaluating a binary treatment, namely whether a student attending SI performs better or worse than a student who does not attend SI. However, in this setting, we also want to draw inferences on the dose-response relationship, namely how does the number of times a student attends SI impact performance in the course. In this paper, we introduce generalized propensity scores (GPS) for analyzing such continuous treatment. We extend recent developments in GPS analyses from the personalized learning literature for evaluating SI engagement on student success. As part of the exposition, we provide a brief review of generalized propensity scores, compare our proposed GPS approaches, present guidelines on how these methods can be applied to educational data, and present R code and illustration for practitioners to use as a template in educational data mining applications.
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DOI:
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发表时间:
2014
期刊:
影响因子:
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作者:
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DOI:
--
发表时间:
2020
期刊:
Educational Data Mining
影响因子:
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DOI:
10.1007/s10758-017-9317-0
发表时间:
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Knowledge and Learning
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DOI:
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发表时间:
2007
期刊:
影响因子:
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作者:
E. Wilde;R. Hollister
通讯作者:
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影响因子:
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作者:
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通讯作者:
Imai, Kosuke