Semiparametric Nonlinear Mixed-Effects Models and Their Applications

Ke, Chunlei; Wang, Yuedong

doi:10.1198/016214501753381913

Cited by 89 publications

(108 citation statements)

References 63 publications

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“…We pooled the data from multiple subjects within the same group using a mixed-effects framework to model B, the group-level baseline concentration, and (␣, ␤), the group-level regression coefficients for the linearized harmonic function. We fitted our model by using restricted maximum likelihood (34) and identified diurnal variation within a group by rejecting ␣ ϭ ␤ ϭ 0 by using an approximate F test (35). Given the three different hormones measured on two different groups of subjects, we adjusted for the six multiple comparisons by using a Bonferonni correction by setting P Ͻ 0.05͞6 ϭ 0.0083 as our nominal cutoff to identify diurnal variation.…”

Section: Diurnal Variability Analysismentioning

confidence: 99%

Alterations in the dynamics of circulating ghrelin, adiponectin, and leptin in human obesity

Yildiz

Suchard

Wong

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

322

219

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Ghrelin plays a key role in the regulation of growth hormone secretion and energy homeostasis. Adiponectin is exclusively secreted by adipose tissue and is abundantly present in the circulation, with important effects on metabolism. We studied five lean and five obese young men [ages: 24.2 ؎ 1.0 (lean) and 21.8 ؎ 1.6 (obese) years (difference not significant); body mass indexes: 35.0 ؎ 1.3 and 23.0 ؎ 0.3 kg͞m 2 (P ‫؍‬ 0.01)], sampled blood every 7 min over 24 h, and measured ghrelin, adiponectin, and leptin in 2,070 samples for a total of 6,210 data points. Circulating 24-h ghrelin showed significant ultradian fluctuations and an orderly pattern of release in lean and obese subjects with similar pulsatility characteristics. Plasma adiponectin concentrations were significantly lower in the obese group, with lower pulse height. In contrast to leptin, which is secreted in an orderly manner, the 24-h patterns of adiponectin were not significantly different from random in both the lean and obese groups. We show here that adipocytes can simultaneously secrete certain hormones, such as leptin, in patterns that are orderly, whereas other hormones, such as adiponectin, are secreted in patterns that appear to be random. The cross-approximate entropy statistic revealed pattern synchrony among ghrelin-leptin, ghrelin-adiponectin, and leptinadiponectin hormone time series in the lean and obese subjects. Plasma ghrelin concentrations showed a nocturnal rise that exceeded the meal-associated increases in lean subjects, and this newly identified nocturnal rise was blunted in the obese. We suggest that the blunting of the nocturnal rise of ghrelin is a biological feature of human obesity.

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Section: Diurnal Variability Analysismentioning

confidence: 99%

Alterations in the dynamics of circulating ghrelin, adiponectin, and leptin in human obesity

Yildiz

Suchard

Wong

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

322

219

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“…The focus has been on both semiparametric (e.g. see Ke and Wang, 2001;Li and Stengos, 1996;Ullah and Roy, 1998) and nonparametric estimation of random effects models (e.g. see Henderson and Ullah, 2005;Lin and Carroll, 2000Lin et al, 2004;Lin and Ying, 2001;Ruckstuhl et al, 2000;Wu and Zhang, 2002).…”

Section: Introductionmentioning

confidence: 99%

Nonparametric estimation and testing of fixed effects panel data models

Henderson

Carroll

2008

Journal of Econometrics

185

147

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In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test between the three alternatives in practice. We further propose a test statistic for testing the null hypothesis of random effects against fixed effects in a nonparametric panel data regression model. Simulations are used to examine the finite sample performance of the proposed estimators and the test statistics.

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“…Taking the truncated spectrum into the frequency domain results in a power spectrum that is dominated strongly by the main features (the bulges) of the reflectance spectrum. A low-dimensional parametric or semiparametric [22,27] non-linear model will suffice to describe these low-frequency features well. However, such models invariably relegate detail at higher frequencies to the residual variance despite the fact that group effects can be statistically significant at higher frequencies.…”

Section: Discussionmentioning

confidence: 99%

An approach for the analysis of vegetation spectra using non-linear mixed modeling of truncated power spectra

et al. 2004

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-Analysis of vegetation spectra is often characterized by an adverse ratio of sample size to number of wavelengths. A reduction in the dimensionality of the spectra is needed to ensure consistent estimates. We propose a reduction based on a non-linear mixed modeling of power spectra transforms of truncated Fourier series representations of vegetation spectra. Two sets of foliage spectral data obtained from balsam fir (Abies balsamea) exposed to different silvicultural regimes and three eucalypt species (Eucalyptus spp.) demonstrate the method. Only the first 42 frequencies in a power spectrum contributed significantly to the variance of a spectrum. Power spectra were dominated by a small number of low frequencies; the influence of frequency was described well by an exponentiated quadratic polynomial model with significant fixed and random effects. Model parameters can be subject to physiological inference and hypothesis testing. nonlinear-mixed model / Fourier transform / power spectra / hypothesis testing / classificationRésumé -Méthode d'analyse des spectres de végétation par modélisation mixte non linéaire des spectres de puissance tronqués. L'analyse des spectres de végétation est souvent caractérisée par un rapport négatif entre la taille de l'échantillon et le nombre de longueurs d'ondes. Une réduction de la dimension des spectres est nécessaire pour garantir des estimations uniformes. Nous proposons une réduction fondée sur une modélisation mixte non linéaire des transformées de puissance spectrale des représentations de séries de Fourier tronquées visant des spectres de végétation. Pour ce faire, nous utilisons deux ensembles de données spectrales du feuillage de sapins baumiers (Abies balsamea) exposés à différents traitements sylvicoles et de trois espèces d'eucalyptus (Eucalyptus spp.). Seules les 42 premières fréquences de puissance spectrale ont contribué de façon appréciable à sa variance. Un petit nombre de basses fréquences dominaient les puissances spectriques ; l'effet de la fréquence a été bien décrit à l'aide d'un modèle polynomial quadratique d'exponentiation comportant des effets fixes et aléatoires appréciables. Les paramètres du modèle peuvent faire l'objet d'analyse de l'hypothèse et d'une inférence physiologique. modèle mixte non-linéaire / transformation Fourier / répartition spectrale / tests des hypothèses / classification

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Semiparametric Nonlinear Mixed-Effects Models and Their Applications

Cited by 89 publications

References 63 publications

Alterations in the dynamics of circulating ghrelin, adiponectin, and leptin in human obesity

Alterations in the dynamics of circulating ghrelin, adiponectin, and leptin in human obesity

Nonparametric estimation and testing of fixed effects panel data models

An approach for the analysis of vegetation spectra using non-linear mixed modeling of truncated power spectra

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