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

• Published in: PLoS computational biology Vol. 17; no. 11; p. e1009585
• Main Authors: Madssen, Torfinn S., Giskeødegård, Guro F., Smilde, Age K., Westerhuis, Johan A.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09.11.2021; Public Library of Science (PLoS)
• Subjects: Analysis; Analysis of variance; Antineoplastic Agents, Immunological - therapeutic use; Bariatric Surgery; Bevacizumab - therapeutic use; Biology and Life Sciences; Breast Neoplasms - drug therapy; Clinical trials; Confidence intervals; Data analysis; Data Interpretation, Statistical; Datasets; Design of experiments; Experimental design; Female; Genomics; Humans; Intervention; Linear models (Statistics); Linear regression models; Longitudinal method; Longitudinal Studies; Medical research; Medicine and Health Sciences; Metabolomics; Methods; Missing data; Multivariate analysis; Physical Sciences; Principal components analysis; Proteomics; Reproducibility of Results; Research and Analysis Methods; Time measurement; Transcriptomics; Variables; Variance analysis; Within-subjects design; Netherlands

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 dat...