Distributional data analysis of accelerometer data from the NHANES database using nonparametric survey regression models

The aim of this paper is twofold. First, a new functional representation of accelerometer data of a distributional nature is introduced to build a complete individualized profile of each subject’s physical activity levels. Second, we extend two nonparametric functional regression models, kernel smoo...

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Bibliographic Details
Published inJournal of the Royal Statistical Society Series C: Applied Statistics Vol. 72; no. 2; pp. 294 - 313
Main Authors Matabuena, Marcos, Petersen, Alexander
Format Journal Article
LanguageEnglish
Published Oxford Oxford University Press 12.05.2023
Subjects
Accelerometers
Data analysis
Physical activity
Polls & surveys
Regression models
Representations
Sampling designs
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Summary:The aim of this paper is twofold. First, a new functional representation of accelerometer data of a distributional nature is introduced to build a complete individualized profile of each subject’s physical activity levels. Second, we extend two nonparametric functional regression models, kernel smoothing and kernel ridge regression, to handle survey data and obtain reliable conclusions about the influence of physical activity. The advantages of the proposed distributional representation are demonstrated through various analyses performed on the NHANES cohort, which possesses a complex sampling design.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0035-9254
1467-9876
DOI:10.1093/jrsssc/qlad007