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Estimating latent trends in multivariate longitudinal data via Parafac2 with functional and structural constraints
1Department of Psychology, University of Minnesota, 75 E River Road, Minneapolis, MN 55455, USA.
Biometrical Journal. Biometrische Zeitschrift
|December 28, 2016
Summary
Longitudinal data analysis using multimode component analysis reveals concerning alcohol consumption trends in the U.S. Despite recommendations, total alcohol intake shows no decrease, indicating a persistent public health issue.
Area of Science:
- Statistics
- Data Science
- Public Health
Background:
- Longitudinal data often involves multiple modes of variation (time, variables, subjects).
- Multimode component analysis is effective for identifying latent trends in longitudinal data.
- Existing models often neglect functional (temporal sequence) and structural (variable-factor relationships) information.
Purpose of the Study:
- To incorporate functional and structural constraints into multimode models (Parafac, Parafac2).
- To elucidate temporal trends in latent constructs within longitudinal data.
- To analyze per capita alcohol consumption trends in the U.S. from 1970-2013.
Main Methods:
- Application of functional and structural constraints within Parafac and Parafac2.
- Utilizing alternating least squares algorithms for model fitting.
- Analysis of longitudinal alcohol consumption data from the U.S. National Institute on Alcohol Abuse and Alcoholism.
Main Results:
- Incorporation of functional and structural information enhances understanding of latent trends.
- Identified temporal and regional trends in beer, spirits, and wine consumption.
- Results indicate Americans exceed recommended alcohol intake levels.
Conclusions:
- Multimode component analysis with functional and structural constraints provides deeper insights into longitudinal data.
- Total alcohol consumption trends in the U.S. have not decreased in the past decade.
- Findings highlight the need for continued monitoring and intervention regarding alcohol consumption.
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