Nutrition of Infants and Preschool Children in the North Central Region of the United States of America1

Eppright, Ercel S.; Fox, H. M.; Fryer, Beth A.; Lamkin, G. H.; Vivian, Virginia M.; Fuller, E. S.

doi:10.1159/000392739

Cited by 57 publications

(6 citation statements)

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“…Approximately two-thirds of parents reported using food as a reward and withholding food, usually dessert, as a punishment (Dennison et al, 2000a;Eppright et al, 1972). When young children were allowed to choose freely from a selection of foods, they selected many non-nutritious foods.…”

Section: Parent and Caregiver Skills Trainingmentioning

confidence: 99%

Handbook of Childhood and Adolescent Obesity

Jelalian¹,

Steele²

2008

Issues in Clinical Child Psychology

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Section: Parent and Caregiver Skills Trainingmentioning

confidence: 99%

Handbook of Childhood and Adolescent Obesity

Jelalian¹,

Steele²

2008

Issues in Clinical Child Psychology

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“…Eubank (1988, pp. 231, 271-272) fits cubic splines to data representing the ratios of weight to height for boys from a study by Eppright et al (1972). Using generalized crossvalidation, he finds estimates = 1.38, t r H ( i ) = 10, and ni = 0.00062.…”

Section: Szmulataonsmentioning

confidence: 99%

Bayesian Nonparametric Modeling Using Mixtures of Triangular Distributions

Perron

Mengersen

2001

Biometrics

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Nonparametric modeling is an indispensable tool in many applications and its formulation in an hierarchical Bayesian context, using the entire posterior distribution rather than particular expectations, increases its flexibility. In this article, the focus is on nonparametric estimation through a mixture of triangular distributions. The optimality of this methodology is addressed and bounds on the accuracy of this approximation are derived. Although our approach is more widely applicable, we focus for simplicity on estimation of a monotone nondecreasing regression on [0, 1] with additive error, effectively approximating the function of interest by a function having a piecewise linear derivative. Computationally accessible methods of estimation are described through an amalgamation of existing Markov chain Monte Carlo algorithms. Simulations and examples illustrate the approach.

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“…Segmented polynomial regression models (in particular continuous two‐phase polynomial regression models) are widely used in practice. The three real datasets from public health (Eppright et al, 1972; Gallant & Fuller, 1973), ecology (Sofaer et al, 2020) and physics (Holst et al, 1996) that will be used to illustrate our proposed methods are shown in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

“…(a) Infant and preschool boys weight‐height ratio by age (Eppright et al, 1972). (b) Proportion of synanthropic song birds versus land use intensity (Sofaer et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Fast grid search and bootstrap‐based inference for continuous two‐phase polynomial regression models

Son

Fong

2020

Environmetrics

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Two‐phase polynomial regression models (Robison, 1964; Fuller, 1969; Gallant and Fuller, 1973; Zhan et al., 1996) are widely used in ecology, public health, and other applied fields to model nonlinear relationships. These models are characterized by the presence of threshold parameters, across which the mean functions are allowed to change. That the threshold is a parameter of the model to be estimated from the data is an essential feature of two‐phase models. It distinguishes them, and more generally, multiphase models, from the spline models and has profound implications for both computation and inference for the models. Estimation of two‐phase polynomial regression models is a nonconvex, nonsmooth optimization problem. Grid search provides high‐quality solutions to the estimation problem, but is very slow when performed by brute force. Building upon our previous work on piecewise linear two‐phase regression models estimation, we develop fast grid search algorithms for two‐phase polynomial regression models and demonstrate their performance. Furthermore, we develop bootstrap‐based pointwise and simultaneous confidence bands for mean functions. Monte Carlo studies are conducted to demonstrate the computational and statistical properties of the proposed methods. Three real datasets are used to help illustrate the application of two‐phase models, with special attention on model choice.

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Nutrition of Infants and Preschool Children in the North Central Region of the United States of America1

Cited by 57 publications

References 0 publications

Handbook of Childhood and Adolescent Obesity

Handbook of Childhood and Adolescent Obesity

Bayesian Nonparametric Modeling Using Mixtures of Triangular Distributions

Fast grid search and bootstrap‐based inference for continuous two‐phase polynomial regression models

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