Author: Lung-fei Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
Book Description
A Numerically Stable Quadrature Procedure for the One-factor Random-component Discrete Choice Model
The Econometrics of Panel Data
Author: Lászlo Mátyás
Publisher: Springer Science & Business Media
ISBN: 3540758925
Category : Business & Economics
Languages : en
Pages : 966
Book Description
This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.
Publisher: Springer Science & Business Media
ISBN: 3540758925
Category : Business & Economics
Languages : en
Pages : 966
Book Description
This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.
Econometric Analysis of Health Data
Author: Andrew M. Jones
Publisher: John Wiley & Sons
ISBN: 9780470841457
Category : Medical
Languages : en
Pages : 252
Book Description
Given extensive use of individual level data in Health Economics, it has become increasingly important to understand the microeconometric techniques available to applied researchers. The purpose of this book is to give readers convenient access to a collection of recent contributions that contain innovative applications of microeconometric methods to data on health and health care. Contributions are selected from papers presented at the European Workshops on Econometrics and Health Economics and published in Health Economics. Topics covered include: * Latent Variables * Unobservable heterogeneity and selection problems * Count data and survival analysis * Flexible and semiparametric estimators for limited dependent variables * Classical and simulation methods for panel data * Publication marks the tenth anniversary of the Workshop series. Doctoral students and researchers in health economics and microeconomics will find this book invaluable. Researchers in related fields such as labour economics and biostatistics will also find the content of use.
Publisher: John Wiley & Sons
ISBN: 9780470841457
Category : Medical
Languages : en
Pages : 252
Book Description
Given extensive use of individual level data in Health Economics, it has become increasingly important to understand the microeconometric techniques available to applied researchers. The purpose of this book is to give readers convenient access to a collection of recent contributions that contain innovative applications of microeconometric methods to data on health and health care. Contributions are selected from papers presented at the European Workshops on Econometrics and Health Economics and published in Health Economics. Topics covered include: * Latent Variables * Unobservable heterogeneity and selection problems * Count data and survival analysis * Flexible and semiparametric estimators for limited dependent variables * Classical and simulation methods for panel data * Publication marks the tenth anniversary of the Workshop series. Doctoral students and researchers in health economics and microeconomics will find this book invaluable. Researchers in related fields such as labour economics and biostatistics will also find the content of use.
Multivariate Generalized Linear Mixed Models Using R
Author: Damon Mark Berridge
Publisher: CRC Press
ISBN: 1439813264
Category : Mathematics
Languages : en
Pages : 306
Book Description
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model estimation, and endogenous variables, along with SabreR commands and examples. Improve Your Longitudinal Study In medical and social science research, MGLMMs help disentangle state dependence from incidental parameters. Focusing on these sophisticated data analysis techniques, this book explains the statistical theory and modeling involved in longitudinal studies. Many examples throughout the text illustrate the analysis of real-world data sets. Exercises, solutions, and other material are available on a supporting website.
Publisher: CRC Press
ISBN: 1439813264
Category : Mathematics
Languages : en
Pages : 306
Book Description
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model estimation, and endogenous variables, along with SabreR commands and examples. Improve Your Longitudinal Study In medical and social science research, MGLMMs help disentangle state dependence from incidental parameters. Focusing on these sophisticated data analysis techniques, this book explains the statistical theory and modeling involved in longitudinal studies. Many examples throughout the text illustrate the analysis of real-world data sets. Exercises, solutions, and other material are available on a supporting website.
Interpolation, Quadrature and Stochastic Integration
Author: Lung-fei Lee
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 32
Book Description
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 32
Book Description