Universal Formulas for Treatment Effects from Noncompliance Data

Alexander A. Balke () and Judea Pearl ()
Additional contact information
Alexander A. Balke: University of California, Cognitive Systems Laboratory
Judea Pearl: University of California, Cognitive Systems Laboratory

A chapter in Lifetime Data: Models in Reliability and Survival Analysis, 1996, pp 39-43 from Springer

Abstract: Abstract This paper establishes formulas that can be used to bound the actual treatment effect in any experimental study in which treatment assignment is random but subject compliance is imperfect. These formulas provide the tightest bounds on the average treatment effect that can be inferred given the distribution of assignments, treatments, and responses. Our results reveal that even with high rates of noncompliance, experimental data can yield significant and sometimes accurate information on the effect of a treatment on the population.

Keywords: Causal Effect; Treatment Assignment; Average Treatment Effect; Tight Bound; Universal Formula (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-5654-8_6

Ordering information: This item can be ordered from
http://www.springer.com/9781475756548

DOI: 10.1007/978-1-4757-5654-8_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().