Partial Compliance, Effect of Treatment on the Treated and Instrumental Variables

被引：1
|
作者：
Forcina, Antonio [1 ]
机构：
[1] Dipartimento Econ Finanza & Stat, I-06100 Perugia, Italy
来源：
CLASSIFICATION AND MULTIVARIATE ANALYSIS FOR COMPLEX DATA STRUCTURES | 2011年
关键词：
CAUSAL INFERENCE; PRINCIPAL STRATIFICATION; MEAN MODELS; NONCOMPLIANCE; TRIALS;
D O I：
10.1007/978-3-642-13312-1_33
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Under the assumption that treatment assignment has no direct effect on the response, a non parametric probabilistic model of the distribution involving the latent confounder under partial compliance leads to a generalized definition of the effect of treatment on the treated and reveals that the instrumental variable estimand equals a suitable average of such causal effects only when certain restrictions hold. An application to a popular data set concerning reduction of cholesterol level is used as an illustration.
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页码：317 / 324
页数：8
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