Propensity Score Matching for Education Data: Worked Examples

被引:13
|
作者
Powell, Marvin G. [1 ]
Hull, Darrell M. [2 ]
Beaujean, A. Alexander [3 ]
机构
[1] George Mason Univ, 4400 Univ Dr,MS6D2,West Bldg,Room 2105, Fairfax, VA 22030 USA
[2] Univ North Texas, Denton, TX USA
[3] Baylor Univ, Waco, TX 76798 USA
来源
JOURNAL OF EXPERIMENTAL EDUCATION | 2020年 / 88卷 / 01期
关键词
Propensity scores; matching; observational study; CAUSAL INFERENCE; MISSING DATA; BIAS; SUBCLASSIFICATION; METHODOLOGY; STATISTICS; BALANCE;
D O I
10.1080/00220973.2018.1541850
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the concept of propensity scores by explaining their theoretical principles and providing two examples of their usefulness within the realm of educational research. Through worked examples, we highlight the effectiveness of propensity scores as a method for reducing bias and increasing the balance between treatment and comparison groups. To aid in the understanding and future use of propensity scores, we provide R syntax for all our analyses.
引用
收藏
页码:145 / 164
页数:20
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