A Method-of-Moments Estimation Procedure for Categorical Quality-of-Life Data with Nonignorable Missingness
作者:
Marco Bonetti,
BernardF. Cole,
RichardD. Gelber,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1999)
卷期:
Volume 94,
issue 448
页码: 1025-1034
ISSN:0162-1459
年代: 1999
DOI:10.1080/01621459.1999.10473855
出版商: Taylor & Francis Group
关键词: Identifiability;Multinomial model;Nonignorable missingness;Quality of life.
数据来源: Taylor
摘要:
Quality-of-life outcomes collected during clinical trials often have considerable amounts of missing data, which, if not appropriately accounted for, may lead to bias in inferences. We introduce a method-of-moments (MM) estimating procedure for a model designed to handle nonignorable missingness arising in categorical data measured on independent populations. The missingness mechanism is assumed to be the same across the populations. We derive necessary and sufficient conditions for the identifiability of the model and fit the model to quality-of-life data collected as part of a breast cancer clinical trial. We compare the MM estimator to the maximum likelihood estimator in a simulation study.
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