Repeated measures ASCA+ for analysis of longitudinal intervention studies with multivariate outcome data.

ABSTRACT: Longitudinal intervention studies with repeated measurements over time are an important type of experimental design in biomedical research. Due to the advent of "omics"-sciences (genomics, transcriptomics, proteomics, metabolomics), longitudinal studies generate increasingly multivariate outcome data. Analysis of such data must take both the longitudinal intervention structure and multivariate nature of the data into account. The ASCA+-framework combines general linear models with principal component analysis and can be used to separate and visualize the multivariate effect of different experimental factors. However, this methodology has not yet been developed for the more complex designs often found in longitudinal intervention studies, which may be unbalanced, involve randomized interven

SUBMITTER: Madssen TS 

PROVIDER: S-EPMC8604364 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature