Projection-based two-sample inference for sparsely observed multivariate functional data.

ABSTRACT: Modern longitudinal studies collect multiple outcomes as the primary endpoints to understand the complex dynamics of the diseases. Oftentimes, especially in clinical trials, the joint variation among the multidimensional responses plays a significant role in assessing the differential characteristics between two or more groups, rather than drawing inferences based on a single outcome. We develop a projection-based two-sample significance test to identify the population-level difference between the multivariate profiles observed under a sparse longitudinal design. The methodology is built upon widely adopted multivariate functional principal component analysis to reduce the dimension of the infinite-dimensional multi-modal functions while preserving the dynamic correlation between the compo

SUBMITTER: Koner S 

PROVIDER: S-EPMC11639128 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature