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Fixed-effects inference and tests of correlation for longitudinal functional data.

ABSTRACT: We propose an inferential framework for fixed effects in longitudinal functional models and introduce tests for the correlation structures induced by the longitudinal sampling procedure. The framework provides a natural extension of standard longitudinal correlation models for scalar observations to functional observations. Using simulation studies, we compare fixed effects estimation under correctly and incorrectly specified correlation structures and also test the longitudinal correlation structure. Finally, we apply the proposed methods to a longitudinal functional dataset on physical activity. The computer code for the proposed method is available at https://github.com/rli20ST758/FILF.

SUBMITTER: Li R

PROVIDER: S-EPMC9283332 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Fixed-effects inference and tests of correlation for longitudinal functional data.

Li Ruonan R Xiao Luo L Smirnova Ekaterina E Cui Erjia E Leroux Andrew A Crainiceanu Ciprian M CM

Statistics in medicine 20220501 17

We propose an inferential framework for fixed effects in longitudinal functional models and introduce tests for the correlation structures induced by the longitudinal sampling procedure. The framework provides a natural extension of standard longitudinal correlation models for scalar observations to functional observations. Using simulation studies, we compare fixed effects estimation under correctly and incorrectly specified correlation structures and also test the longitudinal correlation stru ...[more]

PMID: 35491388

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