A comparison of using weighted distribution and joint modeling for analyzing non-ignorable missing responses

DOI10.1080/03610918.2017.1395043OpenAlexW2765577445MaRDI QIDQ5086186

Esmaile Khorram, Zahra Sadat Meshkani Farahani, Mojtaba Ganjali

Publication date: 1 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2017.1395043

zbMATH Keywords

weighted distributionlength-biasedjoint modelingmissing mechanismmissingness

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric inference (62F99)

Cites Work

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• Models for discrete longitudinal data.
• Joint Models for Longitudinal and Time-to-Event Data
• The common structure of several models for non-ignorable dropout
• Inference and missing data
• Length-Biased Sampling With Right Censoring
• Pattern-Mixture Models for Multivariate Incomplete Data
• Informative Drop-Out in Longitudinal Data Analysis

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