Park, Yeonhee; Su, Zhihua; Zhu, Hongtu Groupwise envelope models for imaging genetic analysis. (English) Zbl 1405.62197 Biometrics 73, No. 4, 1243-1253 (2017). 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. Cited in 4 Documents 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 Keywords:dimension reduction; envelope model; reducing subspace; imaging genetic analysis; multivariate linear regression PDFBibTeX XMLCite \textit{Y. Park} et al., Biometrics 73, No. 4, 1243--1253 (2017; Zbl 1405.62197) Full Text: DOI Link