Semiparametric analyses of cross-over data with repeated measures

被引：2

作者：

Coull, BA

Catalano, PJ

Godleski, JJ

机构：

[1] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA

[2] Dana Farber Canc Inst, Dept Biostat Sci, Boston, MA 02115 USA

[3] Harvard Univ, Sch Publ Hlth, Dept Environm Hlth, Boston, MA 02115 USA

来源：

JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS | 2000年 / 5卷 / 04期

关键词：

autoregressive errors; local regression; longitudinal data; nonparametric regression; partial linear model; smoothing;

D O I：

10.2307/1400658

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A model is proposed to analyze data arising from a cross-over experiment in which measurements on a control and an exposed subject are recorded over time within each crossover period. The model uses locally weighted quadratic regression to control for nuisance temporal trends common to both control and exposed subjects within each period and specifies a first-order autoregressive process to account for dependence among measurements within each longitudinal sequence. We apply the model to a motivating data set in which laboratory animals are exposed to concentrated air particles.

引用

页码：417 / 429

页数：13

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