ROBUST ANALYSIS OF LONGITUDINAL DATA(Statistical Models for Biomedical Research)

    • Fu Bo
    • Department of Statistics and Actuarial Science, The University of Hong Kong
    • Fung Wing K.
    • Department of Statistics and Actuarial Science, The University of Hong Kong
    • He Xuming
    • Department of Statistics, University of Illinois

抄録

Two robust methods for the analysis of longitudinal data are discussed. The marginal linear model with correlated observations within individuals is employed. We summarize literature on robust methods and suggest the modifications of Huggins' and Jung's estimates to simplify the procedure for the analysis of longitudinal data. The small sample behaviours of the two estimates are investigated under various situations by simulation. A real data set is analysed. This paper provides a useful reference for practitioners to the choice of robust methods in the analysis of longitudinal data.

収録刊行物

Journal of the Japanese Society of Computational Statistics   [巻号一覧]

Journal of the Japanese Society of Computational Statistics 15(2), 81-87, 2003-06  [この号の目次]

日本計算機統計学会

参考文献:  12件

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各種コード

  • NII論文ID(NAID) :
    110001235165
  • NII書誌ID(NCID) :
    AA10823693
  • 本文言語コード :
    ENG
  • 資料種別 :
    REV
  • ISSN :
    09152350
  • 収録DB :
    CJP書誌  NII-ELS