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A NONPARAMETRIC MIXED‐EFFECTS MODEL FOR CANCER MORTALITY
Authors:Megu Ohtaki
Abstract: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.
Keywords:cancer mortality  kernel smoothing  local linear approximation  longitudinal count data  mixed‐effects  Poisson regression  time‐varying coefficient
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