Applying Non-negative Matrix Factorization with Covariates to the Longitudinal Data as Growth Curve Model
The study extends Non-negative Matrix Factorization (NMF) to longitudinal data by incorporating covariates, establishing a formal link to the Growth Curve Model (GCM). This allows NMF to use an optimized basis that improves GCM fits when covariate effects are non-negative. The work provides methods for estimating covariate effects and compares NMF's soft clustering against PCA.