The potential for bias in principal causal effect estimation when treatment received depends on a key covariate

DOI10.1214/11-AOAS477zbMath1228.62153arXiv1111.1509OpenAlexW3098198224WikidataQ40775058 ScholiaQ40775058MaRDI QIDQ652349

Corwin M. Zigler, Thomas R. Belin

Publication date: 14 December 2011

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1111.1509

zbMATH Keywords

noncomplianceprincipal stratificationcomplier average causal effectprincipal effect

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Medical applications (general) (92C50) Numerical analysis or methods applied to Markov chains (65C40) General considerations in statistical decision theory (62C05)

Related Items (2)

The potential for bias in principal causal effect estimation when treatment received depends on a key covariate ⋮ A Likelihood-Based Analysis for Relaxing the Exclusion Restriction in Randomized Experiments with Noncompliance

Uses Software

• BayesDA

Cites Work

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