The Generalized Estimating Equation Approach When Data are Not Missing Completely at Random
DOI: 10.1080/01621459.1997.10473653
关键词: Importance sampling 、 Weighting 、 Estimator 、 Statistics 、 Generalized estimating equation 、 Imputation (statistics) 、 Missing data 、 Estimating equations 、 Mathematics 、 Gee
摘要: Abstract We propose two methods for handling missing data in generalized estimating equation (GEE) analyses: mean imputation and multiple imputation. Each provides valid GEE estimates when are at random. Missing outcomes imputed sequentially starting from the outcome nearest time to observed outcome. The estimators kinds of compared with weighting method Robins et al. show that an infinite number replications is asymptotically equivalent applied a stroke study which neurological measured over after but some due death or loss follow up.
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