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文章基本信息

  • 标题:Longitudinal Survey, Nonmonotone, Nonresponse, Imputation, Nonparametric Regression
  • 本地全文:下载
  • 作者:Sarah Pyeye ; Charles K. Syengo ; Leo Odongo
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2016
  • 卷号:06
  • 期号:06
  • 页码:1138-1154
  • DOI:10.4236/ojs.2016.66092
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:The study focuses on the imputation for the longitudinal survey data which often has nonignorable nonrespondents. Local linear regression is used to impute the missing values and then the estimation of the time-dependent finite populations means. The asymptotic properties (unbiasedness and consistency) of the proposed estimator are investigated. Comparisons between different parametric and nonparametric estimators are performed based on the bootstrap standard deviation, mean square error and percentage relative bias. A simulation study is carried out to determine the best performing estimator of the time-dependent finite population means. The simulation results show that local linear regression estimator yields good properties.
  • 关键词:Longitudinal Survey;Nonmonotone;Nonresponse;Imputation;Nonparametric Regression
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