Identifiability of Normal and Normal Mixture Models with Nonignorable Missing Data-Reference-Cited by-同舟云学术

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Identifiability of Normal and Normal Mixture Models with Nonignorable Missing Data

Published:2016-10-01 Issue:516 Volume:111 Page:1673-1683
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Miao Wang¹,Ding Peng²,Geng Zhi³

Affiliation:

1. Beijing International Center for Mathematical Research, Peking University, Beijing, China

2. Department of Statistics, University of California at Berkeley, Berkeley, CA, USA

3. School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing, China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2015.1105808

Reference22 articles.

1. Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing Data

2. Inference on the Order of a Normal Mixture

3. Parametric models for response-biased sampling

4. Bayesian robust inference of sample selection using selection-tmodels

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1. Uncovering the Propensity Identification Problem in Debiased Recommendations;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

2. Identification and Semiparametric Efficiency Theory of Nonignorable Missing Data with a Shadow Variable;ACM / IMS Journal of Data Science;2024-04-08

3. Verifiable identification condition for nonignorable nonresponse data with categorical instrumental variables;Statistical Theory and Related Fields;2024-01-02

4. Group Testing Regression Analysis with Missing Data and Imperfect Tests;Statistica Sinica;2024

5. A Unified Inference Framework for Multiple Imputation Using Martingales;Statistica Sinica;2024

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