Semiparametric Transformation Approach to Estimating Usual Daily Intake Distributions, A
Sarah M. Nusser, Alicia L. Carriquiry, Wayne A. Fuller
September 1992 [92-WP 99]
Nusser, S.M., A.L. Carriquiry, and W. Fuller. 1992. "Semiparametric Transformation Approach to Estimating Usual Daily Intake Distributions, A." Working paper 92-WP 99. Center for Agricultural and Rural Development, Iowa State University.
The distribution of usual intakes of dietary components is important to individuals formulating food policy and to persons designing nutrition education programs. Usual intake of a dietary component for a person is the long run average of daily intakes of that component for that person. Because it is impossible to directly observe usual intake of an individual, it is necessary to develop an estimator of the distribution of usual intakes based on a sample of individuals with a small number of daily observations on each individual. Daily intake data for individuals are nonnegative and often very skewed. Also, there is large day-to-day variation relative to the individual-to-individual variation and the within-individual variance is correlated with the individual means. We suggest a methodology for estimating usual intake distributions that allows for varying degrees of departure from normality and recognizes the measurement error associated with daily dietary intakes. The estimation method contains four steps. First, the original data are standardized by adjusting for weekday and interview sequence effects. Second, the daily intake data are transformed to normality using a combination of power and grafted polynomial transformations. Third, using a normal components-of-variance model, the distribution of usual intakes is constructed for the transformed data. Finally, a transformation of normal usual intakes to the original scale is defined. The approach works well for a set of dietary components selected from the 1985-1986 Continuing Survey of Food intakes by Individuals data. The selected components display a range of distributional shapes.
Keywords: Measurement error models, nutritional status, Continuing Survey of Food Intakes by Individuals, density estimation.