Bayesian sensitivity analyses for longitudinal data with dropouts that are potentially missing not at random: A high dimensional pattern‐mixture model-Reference-Cited by-同舟云学术

Bayesian sensitivity analyses for longitudinal data with dropouts that are potentially missing not at random: A high dimensional pattern‐mixture model

Published:2021-06-02 Issue:21 Volume:40 Page:4609-4628
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Kaciroti Niko A.¹²^ORCID,Little Roderick J.A.¹

Affiliation:

1. Department of Biostatistics, School of Public Health University of Michigan Ann Arbor Michigan USA

2. Department of Pediatrics, Medical School University of Michigan Ann Arbor Michigan USA

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9083

Reference37 articles.

1. Pattern-Mixture Models for Multivariate Incomplete Data

2. Statistical Analysis with Missing Data, Third Edition

3. Semiparametric Regression for Repeated Outcomes with Nonignorable Nonresponse

4. Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models

5. Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes

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