全球智库信息集成服务系统(G2TT): Horseshoes, Hand Grenades, and Treatment Effects? Reassessing Whether Nonexperimental Estimators are Biased

G2TT

来源类型	Publication
	Horseshoes, Hand Grenades, and Treatment Effects? Reassessing Whether Nonexperimental Estimators are Biased
	Kenneth Fortson; Philip Gleason; Emma Kopa; and Natalya Verbitsky-Savitz
发表日期	2015-02-28
出版者	Economics of Education Review, vol. 44
出版年	2015
语种	英语
概述	Randomized controlled trials (RCTs) are considered the gold standard in estimating treatment effects. When an RCT is infeasible, regression modeling or statistical matching are often used instead.",
摘要	Highlights: Tests bias in nonexperimental regression, propensity score approaches. Rich pre-intervention data greatly reduce bias. Some bias may remain. Randomized controlled trials (RCTs) are considered the gold standard in estimating treatment effects. When an RCT is infeasible, regression modeling or statistical matching are often used instead. Nonexperimental methods such as these could produce unbiased estimates if the underlying assumptions hold, but those assumptions are usually not testable. Most prior studies testing nonexperimental designs find that they fail to produce unbiased estimates, but these studies have examined weaker evaluation designs. The present study addresses these limitations using student-level data based on a large-scale RCT of charter schools for which standardized achievement tests are the key outcome measure. The use of baseline data that are strongly predictive of the key outcome measures considerably reduces but might not completely eliminate bias.
URL	https://www.mathematica.org/our-publications-and-findings/publications/horseshoes-hand-grenades-and-treatment-effects-reassessing-whether-nonexperimental-estimators
来源智库	Mathematica Policy Research (United States)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/488007
推荐引用方式 GB/T 7714	Kenneth Fortson,Philip Gleason,Emma Kopa,et al. Horseshoes, Hand Grenades, and Treatment Effects? Reassessing Whether Nonexperimental Estimators are Biased. 2015.