A Comparison of Mean-Based and Quantile Regression Methods for Analyzing Self-Report Dietary Intake Data
Joint Authors
Reninger, Belinda
Vidoni, Michelle L.
Lee, MinJae
Source
Journal of Probability and Statistics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-03
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
In mean-based approaches to dietary data analysis, it is possible for potentially important associations at the tails of the intake distribution, where inadequacy or excess is greatest, to be obscured due to unobserved heterogeneity.
Participants in the upper or lower tails of dietary intake data will potentially have the greatest change in their behavior when presented with a health behavior intervention; thus, alternative statistical methods to modeling these relationships are needed to fully describe the impact of the intervention.
Using data from Tu Salud ¡Si Cuenta! (Your Health Matters!) at Home Intervention, we aimed to compare traditional mean-based regression to quantile regression for describing the impact of a health behavior intervention on healthy and unhealthy eating indices.
The mean-based regression model identified no differences in dietary intake between intervention and standard care groups.
In contrast, the quantile regression indicated a nonconstant relationship between the unhealthy eating index and study groups at the upper tail of the unhealthy eating index distribution.
The traditional mean-based linear regression was unable to fully describe the intervention effect on healthy and unhealthy eating, resulting in a limited understanding of the association.
American Psychological Association (APA)
Vidoni, Michelle L.& Reninger, Belinda& Lee, MinJae. 2019. A Comparison of Mean-Based and Quantile Regression Methods for Analyzing Self-Report Dietary Intake Data. Journal of Probability and Statistics،Vol. 2019, no. 2019, pp.1-5.
https://search.emarefa.net/detail/BIM-1186894
Modern Language Association (MLA)
Vidoni, Michelle L.…[et al.]. A Comparison of Mean-Based and Quantile Regression Methods for Analyzing Self-Report Dietary Intake Data. Journal of Probability and Statistics No. 2019 (2019), pp.1-5.
https://search.emarefa.net/detail/BIM-1186894
American Medical Association (AMA)
Vidoni, Michelle L.& Reninger, Belinda& Lee, MinJae. A Comparison of Mean-Based and Quantile Regression Methods for Analyzing Self-Report Dietary Intake Data. Journal of Probability and Statistics. 2019. Vol. 2019, no. 2019, pp.1-5.
https://search.emarefa.net/detail/BIM-1186894
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186894