An analysis of covariance model where the covariate effect is assumed only to be smooth is considered. The possibility of different shapes of covariate effect in different groups is also allowed and tests of equality and of parallelism across groups are constructed. These are implemented using Gasser-Muller smoothing, whose properties enable problems of bias to be avoided. Accurate moment-based approximations are available for the distribution of each test statistic. Some data on Spanish Onions are used to contrast the non-parametric approach with that of a nonlinear, but parametric, model. A simulation study is also used to explore the properties of the non-parametric tests.
机构:
Peking Univ, Sch Math Sci, Beijing 100871, Peoples R ChinaPeking Univ, Sch Math Sci, Beijing 100871, Peoples R China
Yin, Jianxin
Geng, Zhi
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Peking Univ, Sch Math Sci, Beijing 100871, Peoples R ChinaPeking Univ, Sch Math Sci, Beijing 100871, Peoples R China
Geng, Zhi
Li, Runze
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Penn State Univ, Dept Stat, University Pk, PA 16802 USA
Penn State Univ, Methodol Ctr, University Pk, PA 16802 USAPeking Univ, Sch Math Sci, Beijing 100871, Peoples R China
Li, Runze
Wang, Hansheng
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Peking Univ, Grad Sch Management, Beijing 100871, Peoples R ChinaPeking Univ, Sch Math Sci, Beijing 100871, Peoples R China
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Univ Colorado, Dept Math & Stat Sci, Denver, CO 80217 USAUniv Colorado, Dept Math & Stat Sci, Denver, CO 80217 USA
Culpepper, Steven Andrew
Aguinis, Herman
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Indiana Univ, Kelley Sch Business, Dept Management & Entrepreneurship, Bloomington, IN 47405 USAUniv Colorado, Dept Math & Stat Sci, Denver, CO 80217 USA