A method-of-moments estimation procedure for categorical quality-of-life data with nonignorable missingness

被引：8

作者：

Bonetti, M ^{[1
]}

Cole, BF

Gelber, RD

机构：

[1] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA

[2] Dana Farber Canc Inst, Boston, MA 02115 USA

[3] Dartmouth Med Sch, Epidemiol & Biostat Sect, Lebanon, NH 03756 USA

[4] Harvard Univ, Sch Publ Hlth, Dana Farber Canc Inst, Dept Biostat Sci, Boston, MA 02115 USA

[5] Harvard Univ, Sch Med, Boston, MA 02115 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 1999年 / 94卷 / 448期

关键词：

identifiability; multinomial model; nonignorable missingness; quality of life;

D O I：

10.2307/2669916

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

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.

引用

页码：1025 / 1034

页数：10

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