Australian & New Zealand Journal of Statistics


Journal Article

  • Author(s): Tetsuji Tonda, Kenichi Satoh, Teruyuki Nakayama, Kota Katanoda, Tomotaka Sobue, Megu Ohtaki
  • Article first published online: 15 Jul 2011
  • DOI: 10.1111/j.1467-842X.2011.00615.x
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There are several ways to handle within‐subject correlations with a longitudinal discrete outcome, such as mortality. The most frequently used models are either marginal or random‐effects types. This paper deals with a random‐effects‐based approach. We propose a nonparametric regression model having time‐varying mixed effects for longitudinal cancer mortality data. The time‐varying mixed effects in the proposed model are estimated by combining kernel‐smoothing techniques and a growth‐curve model. As an illustration based on real data, we apply the proposed method to a set of prefecture‐specific data on mortality from large‐bowel cancer in Japan.

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