Estimating Equations Inference With Missing Data
文献类型：期刊论文
| 作者 | Zhou, Yong1,2 ; Wan, Alan T. K.3; Wang, Xiaojing2
|
| 刊名 | JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
 |
| 出版日期 | 2008-09-01 |
| 卷号 | 103期号:483页码:1187-1199 |
| 关键词 | Empirical likelihood Estimating equations Generalized method of moments Kernel regression Missing at random Reduced dimension |
| ISSN号 | 0162-1459 |
| DOI | 10.1198/016214508000000535 |
| 英文摘要 | There is a large and growing body of literature on estimating equation (EE) as an estimation approach. One basic property of EE that has been universely adopted in practice is that of unbiasedness, and there are deep conceptual reasons why unbiasedness is a desirable EE characteristic. This article deals with inference from EEs generally leads to EEs that are biased and thus, violates a basic assumption of the EE approach. The main contribution of this article is that it goes beyond existing imputation methods and proposes a procedure whereby one mitigates the effects of missing data through a reformation of EEs imputed through a kernel regression method. These (modified) EEs then constitute a basis for inference by the generalized method of moments (GMM) and empirical likelihood (EL). Asymptotic properties of the GMM and EL estimators of the unknown parameters are derived and analyzed. Unlike most of the literature, which deals with missingness in either covariate values or response data, our method allows for missingness in both sets of variables. Another important strength of our approach is that it allows auxiliary information to be handled successfully. We illustrate the method using a well-known wormy-fruits dataset and data from a study on Duchenne muscular dystrophy detection and compare our results with several existing methods via a simulation study. |
| 资助项目 | National Natural Science Foundation of China (NSFC)[10628104] ; National Natural Science Foundation of China (NSFC)[10731010] ; National Basic Research Progam[2007CB814902] ; Creative Research Groups of China[10721101] ; Hong Kong Research Grant Council[U 102807] |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000260193700029 |
| 出版者 | AMER STATISTICAL ASSOC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/6976]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | Zhou, Yong |
| 作者单位 | 1.Shanghai Univ Finance & Econ, Dept Stat, Shanghai 200433, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 3.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhou, Yong,Wan, Alan T. K.,Wang, Xiaojing. Estimating Equations Inference With Missing Data[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION,2008,103(483):1187-1199. |
| APA | Zhou, Yong,Wan, Alan T. K.,&Wang, Xiaojing.(2008).Estimating Equations Inference With Missing Data.JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION,103(483),1187-1199. |
| MLA | Zhou, Yong,et al."Estimating Equations Inference With Missing Data".JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 103.483(2008):1187-1199. |
入库方式： OAI收割
来源：数学与系统科学研究院
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