Applied Health Economics, Second Edition |
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Comment from the Stata technical groupApplied Health Economics, Second Edition, by Andrew Jones, Nigel Rice, Teresa Bago d’Uva, and Silvia Balia, shows how to summarize and analyze health-economic data with Stata. The authors teach topics in health economics by defining and asking real questions of real data with Stata. The book includes all the Stata code used in the analyses, and the authors carefully interpret the output. Applied Health Economics lives up to its name by teaching thorough application. This book is an excellent choice for anyone interested in empirical health economics. It offers a nice introduction for graduate students and useful discussions and modeling strategies for more advanced researchers. The wealth of Stata examples makes the book an outstanding resource to researchers analyzing health-economic data with Stata. The second edition has been updated throughout to reflect recent enhancements to Stata. The second edition also contains two timely new chapters on describing and modeling health care costs. Applied Health Economics is nicely organized into parts, which correspond to data types, and chapters within each part, which focus on particular topics in health economics. The coverage is thorough, as the table of contents below makes clear. |
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Table of contentsView table of contents >> Part I
Describing and summarising data
1 Data and survey design
1.1 The Health and Lifestyle Survey
1.2 The British Household Panel Survey 1.3 The European Community Household Panel 1.4 The US Medical Expenditure Panel Survey 1.5 Survey of Health, Ageing and Retirement in Europe 1.6 Overview 2 Describing the dynamics of health
2.1 Introduction
2.2 Graphical analysis 2.3 Tabulating the data 2.4 Overview 3 Describing health care costs
3.1 Introduction
3.2 Data description 3.3 Modelling health care cost data 3.4 Linear regression models 3.5 Overview Part II
Categorical data
4 Reporting heterogeneity in health
4.1 Introduction
4.2 Data 4.3 Standard analysis 4.4 Using vignettes 4.5 Overview Appendix 5 Health and lifestyles
5.1 Introduction
5.2 HALS data and sample 5.3 Descriptive analysis 5.4 Estimation strategy and results 5.5 Overview Part III
Duration Data
6 Smoking and mortality
6.1 Introduction
6.2 Basic concepts of duration analysis 6.3 The HALS data 6.4 Duration data in HALS 6.5 Descriptive statistics 6.6 Duration models 6.7 Overview 7 Health and retirement
7.1 Introduction
7.2 Preparing and summarising the data 7.3 Dealing with self-reported health 7.4 Empirical approach to duration modelling 7.5 Stock sampling and discrete-time hazard analysis 7.6 Overview Part IV
Panel data
8 Health and wages
8.1 Introduction
8.2 BHPS sample and variables 8.3 Empirical model and estimation 8.4 Overview Appendix 9 Modelling the dynamics of health
9.1 Introduction
9.2 Static models 9.3 Dynamic models 9.4 Overview 10 Non-response and attrition bias
10.1 Introduction
10.2 Testing for non-response bias 10.3 Estimation 10.4 Overview Appendix Part V
Health care data
11 Models for count data
11.1 Introduction
11.2 The Poisson model 11.3 The negative binomial model 11.4 Zero-inflated models 11.5 Hurdle models 11.6 Finite mixture/latent class models 11.7 Latent class models for panel data 11.8 Overview Appendix 12 Modelling health care costs
12.1 Introduction
12.2 Exponential conditional mean models 12.3 Generalised linear models 12.4 Finite mixture models 12.5 Comparing model performance 12.6 Overview Bibliography
Index
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