Functional Mixed Processes Models
Introduction
The aim of this tool is to implement a functional analysis pipeline, for the joint analysis of longitudinally measured functional data and clinical data, for example age, gender and disease status. FMPM consists of a functional mixed effects model for characterizing the association of functional response with covariates of interest by incorporating complex spatial–temporal correlation structure, an efficient method for spatially smoothing varying coefficient functions, an estimation method for estimating the spatial– temporal correlation structure, a test procedure with local and global test statistics for testing hypotheses of interest associated with functional response, and a simultaneous confidence band for quantifying the uncertainty in the estimated coefficient functions.
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References
1. Yuan, Y., Gilmore, J. H., Geng, X. J., Styner, M., Chen, K. H., Wang, J. L., and Zhu, H. T. FMEM: Functional mixed effects modeling for the analysis of longitudinal white matter Tract data. NeuroImage, 2014;84:753-764.
2. Yuan, Y., Gilmore, J. H., Geng, X. J., Styner, M., Chen, K. H., Wang, J. L., and Zhu, H. T. A longitudinal functional analysis framework for analysis of white matter tract statistics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013;7917 LNCS:220-231.