A NONPARAMETRIC MIXED-EFFECTS MODEL FOR CANCER MORTALITY

被引：2

作者：

Tonda, Tetsuji ^{[1
]}

Satoh, Kenichi ^{[1
]}

Nakayama, Teruyuki ^{[2
]}

Katanoda, Kota ^{[3
]}

Sobue, Tomotaka ^{[3
]}

Ohtaki, Megu ^{[1
]}

机构：

[1] Hiroshima Univ, Res Inst Radiat Biol & Med, Minami Ku, Hiroshima 7348551, Japan

[2] Int Univ Hlth & Welf, Fac Nursing, Chuo Ku, Fukuoka 8100072, Japan

[3] Natl Canc Ctr, Res Ctr Canc Prevent & Screening, Chuo Ku, Tokyo 1040045, Japan

来源：

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS | 2011年 / 53卷 / 02期

关键词：

cancer mortality; kernel smoothing; local linear approximation; longitudinal count data; mixed-effects; Poisson regression; time-varying coefficient; VARYING-COEFFICIENT MODELS; LIKELIHOOD; REGRESSION; RADIATION; INFERENCE;

D O I：

10.1111/j.1467-842X.2011.00615.x

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：247 / 256

页数：10

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