The Experts below are selected from a list of 11412 Experts worldwide ranked by ideXlab platform
Daniel A. Weinberg - One of the best experts on this subject based on the ideXlab platform.
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healthcare coinsurance Elasticity Coefficient estimation using monthly cross sectional time series claims data
Health Economics, 2017Co-Authors: John F. Scoggins, Daniel A. WeinbergAbstract:Published estimates of the healthcare coinsurance Elasticity Coefficient have typically relied on annual observations of individual healthcare expenditures even though health plan membership and expenditures are traditionally reported in monthly units and several studies have stressed the need for demand models to recognize the episodic nature of healthcare. Summing individual healthcare expenditures into annual observations complicates two common challenges of statistical inference, heteroscedasticity, and regressor endogeneity. This paper estimates the Elasticity Coefficient using a monthly panel data model that addresses the heteroscedasticity and endogeneity problems with relative ease. Healthcare claims data from employees of King County, Washington, during 2005 to 2011 were used to estimate the mean point Elasticity Coefficient: -0.314 (0.015 standard error) to -0.145 (0.015 standard error) depending on model specification. These estimates bracket the -0.2 point estimate (range: -0.22 to -0.17) derived from the famous Rand Health Insurance Experiment. Copyright © 2016 John Wiley & Sons, Ltd.
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Healthcare Coinsurance Elasticity Coefficient Estimation Using Monthly Cross‐sectional, Time‐series Claims Data
Health economics, 2016Co-Authors: John F. Scoggins, Daniel A. WeinbergAbstract:Published estimates of the healthcare coinsurance Elasticity Coefficient have typically relied on annual observations of individual healthcare expenditures even though health plan membership and expenditures are traditionally reported in monthly units and several studies have stressed the need for demand models to recognize the episodic nature of healthcare. Summing individual healthcare expenditures into annual observations complicates two common challenges of statistical inference, heteroscedasticity, and regressor endogeneity. This paper estimates the Elasticity Coefficient using a monthly panel data model that addresses the heteroscedasticity and endogeneity problems with relative ease. Healthcare claims data from employees of King County, Washington, during 2005 to 2011 were used to estimate the mean point Elasticity Coefficient: -0.314 (0.015 standard error) to -0.145 (0.015 standard error) depending on model specification. These estimates bracket the -0.2 point estimate (range: -0.22 to -0.17) derived from the famous Rand Health Insurance Experiment. Copyright © 2016 John Wiley & Sons, Ltd.
John F. Scoggins - One of the best experts on this subject based on the ideXlab platform.
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healthcare coinsurance Elasticity Coefficient estimation using monthly cross sectional time series claims data
Health Economics, 2017Co-Authors: John F. Scoggins, Daniel A. WeinbergAbstract:Published estimates of the healthcare coinsurance Elasticity Coefficient have typically relied on annual observations of individual healthcare expenditures even though health plan membership and expenditures are traditionally reported in monthly units and several studies have stressed the need for demand models to recognize the episodic nature of healthcare. Summing individual healthcare expenditures into annual observations complicates two common challenges of statistical inference, heteroscedasticity, and regressor endogeneity. This paper estimates the Elasticity Coefficient using a monthly panel data model that addresses the heteroscedasticity and endogeneity problems with relative ease. Healthcare claims data from employees of King County, Washington, during 2005 to 2011 were used to estimate the mean point Elasticity Coefficient: -0.314 (0.015 standard error) to -0.145 (0.015 standard error) depending on model specification. These estimates bracket the -0.2 point estimate (range: -0.22 to -0.17) derived from the famous Rand Health Insurance Experiment. Copyright © 2016 John Wiley & Sons, Ltd.
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Healthcare Coinsurance Elasticity Coefficient Estimation Using Monthly Cross‐sectional, Time‐series Claims Data
Health economics, 2016Co-Authors: John F. Scoggins, Daniel A. WeinbergAbstract:Published estimates of the healthcare coinsurance Elasticity Coefficient have typically relied on annual observations of individual healthcare expenditures even though health plan membership and expenditures are traditionally reported in monthly units and several studies have stressed the need for demand models to recognize the episodic nature of healthcare. Summing individual healthcare expenditures into annual observations complicates two common challenges of statistical inference, heteroscedasticity, and regressor endogeneity. This paper estimates the Elasticity Coefficient using a monthly panel data model that addresses the heteroscedasticity and endogeneity problems with relative ease. Healthcare claims data from employees of King County, Washington, during 2005 to 2011 were used to estimate the mean point Elasticity Coefficient: -0.314 (0.015 standard error) to -0.145 (0.015 standard error) depending on model specification. These estimates bracket the -0.2 point estimate (range: -0.22 to -0.17) derived from the famous Rand Health Insurance Experiment. Copyright © 2016 John Wiley & Sons, Ltd.
Song Jiang - One of the best experts on this subject based on the ideXlab platform.
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on stabilizing effect of Elasticity in the rayleigh taylor problem of stratified viscoelastic fluids
Journal of Functional Analysis, 2017Co-Authors: Fei Jiang, Song JiangAbstract:Abstract We investigate the stabilizing effect of Elasticity in the Rayleigh–Taylor (RT) problem of stratified immiscible viscoelastic fluids, separated by a free interface and in the presence of a uniform gravitational field, in a horizontally periodic domain where the velocities of the fluids are non-slip on both upper and lower fixed flat boundaries, while the internal surface tension is omitted. We establish a discriminant C r for the stability of the stratified viscoelastic RT problem. More precisely, if C r 1 , then the stratified viscoelastic RT equilibrium state is exponentially stable. This means that a sufficiently large Elasticity Coefficient has stabilizing effect so that it can inhibit viscoelastic RT instability. On the other hand, if C r > 1 , then we show that the RT equilibrium state is linearly unstable in the Hadamard sense. Moreover, for the case of a nonhomogeneous incompressible viscoelastic fluid, the condition C r > 1 will lead to the nonlinear instability of the RT equilibrium state; and this shows that the RT instability still occurs in viscoelastic fluids when the Elasticity Coefficient is small.
Fei Jiang - One of the best experts on this subject based on the ideXlab platform.
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on stabilizing effect of Elasticity in the rayleigh taylor problem of stratified viscoelastic fluids
Journal of Functional Analysis, 2017Co-Authors: Fei Jiang, Song JiangAbstract:Abstract We investigate the stabilizing effect of Elasticity in the Rayleigh–Taylor (RT) problem of stratified immiscible viscoelastic fluids, separated by a free interface and in the presence of a uniform gravitational field, in a horizontally periodic domain where the velocities of the fluids are non-slip on both upper and lower fixed flat boundaries, while the internal surface tension is omitted. We establish a discriminant C r for the stability of the stratified viscoelastic RT problem. More precisely, if C r 1 , then the stratified viscoelastic RT equilibrium state is exponentially stable. This means that a sufficiently large Elasticity Coefficient has stabilizing effect so that it can inhibit viscoelastic RT instability. On the other hand, if C r > 1 , then we show that the RT equilibrium state is linearly unstable in the Hadamard sense. Moreover, for the case of a nonhomogeneous incompressible viscoelastic fluid, the condition C r > 1 will lead to the nonlinear instability of the RT equilibrium state; and this shows that the RT instability still occurs in viscoelastic fluids when the Elasticity Coefficient is small.
Siegfried Hess - One of the best experts on this subject based on the ideXlab platform.
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Direct computation of the twist elastic Coefficient of a nematic liquid crystal via Monte Carlo simulations.
Physical review letters, 2005Co-Authors: Haiko Steuer, Siegfried HessAbstract:A direct method for the computation of the twist Frank Elasticity Coefficient of a nematic liquid crystal is presented. The method, suitable for numerical calculations, is tested and applied in Monte Carlo simulations for a model system. The dependence of the Elasticity Coefficient on the temperature and density and its relation to the nematic order parameter are analyzed and discussed.