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Groupwise envelope models for imaging genetic analysis. (English) Zbl 1405.62197

Summary: Motivated by searching for associations between genetic variants and brain imaging phenotypes, the aim of this article is to develop a groupwise envelope model for multivariate linear regression in order to establish the association between both multivariate responses and covariates. The groupwise envelope model allows for both distinct regression coefficients and distinct error structures for different groups. Statistically, the proposed envelope model can dramatically improve efficiency of tests and of estimation. Theoretical properties of the proposed model are established. Numerical experiments as well as the analysis of an imaging genetic data set obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study show the effectiveness of the model in efficient estimation. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
92D10 Genetics and epigenetics
62J05 Linear regression; mixed models
62H12 Estimation in multivariate analysis
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