Multiply Robust Weighted Generalized Estimating Equations for Incomplete Longitudinal Binary Data Using Empirical Likelihood-Reference-Cited by-同舟云学术

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Multiply Robust Weighted Generalized Estimating Equations for Incomplete Longitudinal Binary Data Using Empirical Likelihood

Published:2023-04-18 Issue:1 Volume:16 Page:116-129
ISSN:1946-6315
Container-title:Statistics in Biopharmaceutical Research
language:en
Short-container-title:Statistics in Biopharmaceutical Research

Author:

Komazaki Hiroshi¹²^ORCID,Doi Masaaki³^ORCID,Yonemoto Naohiro⁴⁵^ORCID,Sato Tosiya¹^ORCID

Affiliation:

1. Department of Biostatistics, Kyoto University School of Public Health, Kyoto, Japan

2. Clinical Development Department, Maruho Co., Ltd, Kyoto, Japan

3. Data Science, Ono Pharmaceutical Co., Ltd., Osaka, Japan

4. Department of Neuropsychopharmacology, National Center of Neurology and Psychiatry, Tokyo, Japan

5. Department of Public Health, Juntendo University School of Medicine, Bunkyo, Tokyo, Japan

Funder

Japan Agency for Medical Research and Development

Publisher

Informa UK Limited

Subject

Pharmaceutical Science,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/19466315.2023.2191990

Reference23 articles.

1. Doubly Robust Estimation in Missing Data and Causal Inference Models

2. Calibration of the empirical likelihood method for a vector mean

3. Regression Models for Longitudinal Binary Responses with Informative Drop-Outs

4. Statistical Foundations for Model-Based Adjustments

5. Multiply Robust Estimation in Regression Analysis With Missing Data

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