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Fitting a linear model to survey data when the long-term average daily intake of a dietary component is an explanatory variable

Verbesserung eines linearen Modells von Längsschnittdaten zur Nahrungsmittelaufnahme von diätetischen Komponenten als erklärende Variable von Gesundheit
[journal article]

Kott, Phillip S.; Guenther, Patricia M.; Wagstaff, David A.; Juan, WenYen; Kranz, Sibylle

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Please use the following Persistent Identifier (PID) to cite this document:http://dx.doi.org/10.18148/srm/2009.v3i3.2568

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Abstract "The National Health and Nutrition Examination Survey (NHANES) collects information on both dietary intake and health conditions from a complex sample of individuals in the US. Instrumental-variable regression can be used to model an individual's health-related attribute as a linear function of explanatory variables including the average daily intake of dietary components. This overcomes the apparent limitation of the NHANES collecting dietary intake data on only two days per sampled individual because the averages of two days per individual exhibit considerable intra-individual variability. Readily available software routines can perform survey-sensitive instrumental-variable regression with data like that collected by the NHANES, but the relevant quantitative literature is not clear about what parameters these routines are actually estimating. The authors fit the long-term (usual) serum beta-carotene level of a population of women aged 20-64 to a linear function of each woman's long-term average (usual) daily beta-carotene intake from food and other explanatory variables using survey-sensitive instrumental regression and provide two interpretations of the results." (author's abstract)
Keywords United States of America; food; food; nutrition; nutrition-related illness; behavior; health; health consequences; remuneration for members of parliament; woman; age; life expectancy; regression analysis; mean; North America
Classification Research Design; Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods; Health Policy
Document language English
Publication Year 2009
Page/Pages p. 157-165
Journal Survey Research Methods, 3 (2009) 3
Status Published Version; peer reviewed
Licence Deposit Licence - No Redistribution, No Modifications