Estimating Varying Coefficients for Longitudinal Data without Specifying Spatial-Temporal Baseline Trend

• Tonda Tetsuji

  Faculty of Management and Information Systems, Prefectural University of Hiroshima

• Satoh Kenichi

  Research Institute for Radiation Biology and Medicine, Hiroshima University

抄録

In this paper we develop a method for estimating varying coefficients on effects of covariates without modeling the shape of the spatial-temporal baseline trend. We consider the situation where primary interest is in the effects of covariates and the spatial-temporal baseline trend, though non-negligible, is of secondary interest. This is similar to the situation with the Coxproportional hazards model in survival analysis. Basis functions are used to model the shapes of the varying coefficients, but no particular shape is assumed for the spatial-temporal baseline trend. After the effects of covariates are evaluated, estimates of the spatial-temporal baseline trend can be obtained nonparametrically.

収録刊行物

• ＪＯＵＲＮＡＬ　ＯＦ　ＴＨＥ　ＪＡＰＡＮ　ＳＴＡＴＩＳＴＩＣＡＬ　ＳＯＣＩＥＴＹ

  ＪＯＵＲＮＡＬ　ＯＦ　ＴＨＥ　ＪＡＰＡＮ　ＳＴＡＴＩＳＴＩＣＡＬ　ＳＯＣＩＥＴＹ 47 (1), 1-12, 2017

  日本統計学会

キーワード

• Extended Growth curve model
• mixture of GMANOVA and MANOVA model
• nuisance parameter
• simultaneous confidence interval
• spatial-temporal baseline trend
• varying coefficient

詳細情報

• CRID: 1390282680264027904
• NII論文ID: 130006292366
• NII書誌ID: AA1105098X
• DOI: 10.14490/jjss.47.1
• ISSN: 13486365
• ISSN: 18822754
• NDL書誌ID: 028385909
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I028385909
• Web Site: https://www.jstage.jst.go.jp/article/jjss/47/1/47_1/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可