Estimation of causal effects using instrumental variables with nonignorable missing covariates: application to effect of type of delivery NICU on premature infants

DOI10.1214/13-AOAS699zbMath1454.62422arXiv1404.2477OpenAlexW3105553675MaRDI QIDQ2453655

Dylan S. Small, Fan Yang, Scott A. Lorch

Publication date: 10 June 2014

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

Full work available at URL: https://arxiv.org/abs/1404.2477

zbMATH Keywords

instrumental variablesensitivity analysiscausal inferencenonignorable missing data

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (6)

Semiparametric Inference of Causal Effect with Nonignorable Missing Confounders ⋮ Instrumental variable analysis for cost outcome: Application to the effect of primary care visit on medical cost among low‐income adults ⋮ Likelihood identifiability and parameter estimation with nonignorable missing data ⋮ Instrumental variable estimation with a stochastic monotonicity assumption ⋮ Estimation of causal effects using instrumental variables with nonignorable missing covariates: application to effect of type of delivery NICU on premature infants ⋮ Bayesian Scalar on Image Regression With Nonignorable Nonresponse

Uses Software

• MICE

Cites Work

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• Identification of Causal Effects Using Instrumental Variables
• Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing Data
• An Extended General Location Model for Causal Inferences from Data Subject to Noncompliance and Missing Values
• Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes
• Building a Stronger Instrument in an Observational Study of Perinatal Care for Premature Infants
• Analyzing a randomized trial on breast self-examination with noncompliance and missing outcomes
• Multivariate Correlation Models with Mixed Discrete and Continuous Variables

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