Gánh nặng bệnh tật
và chấn thương
ở Việt Nam 2008 NHÀ XUẤT BẢN Y HỌC
HÀ NỘI - 2011 Dự án VINE
Tác giả
ThS. Nguyễn Thị Trang Nhung, Trường Đại học Y tế Công cộng, Việt Nam
CN. Trần Khánh Long, Trường Đại học Y tế Công cộng, Việt Nam
CN. Bùi Ngọc Linh, Trường Đại học Y tế Công cộng, Việt Nam
GS. TS. Theo Vos, Trường Sức khỏe dân số, Đại học Queensland, Úc
TS. Ngô Đức Anh, Trường Sức khỏe dân số, Đại học Queensland, Úc
TS. Nguyễn Thanh Hương, Trường Đại học Y tế Công cộng, Việt Nam
Epidemiology is a subject of growing importance, as witnessed by its role in the description and prediction of the impact of new diseases such as AIDS and new-variant CJD.Epidemiology: Study Design and Data Analysis covers the whole spectrum of standard analytical techniques used in epidemiology, from descriptive techniques in report writing to model diagnostics from generalized linear models. The author discusses the advantages, disadvantages, and alternatives to case-control, cohort and intervention studies and details such crucial concepts as incidence, prevalence, confounding and interaction. Many exercises are provided, based on real epidemiological data sets collected from all over the world. The data sets are also available on an associated web site. Epidemiology: Study Design and Data Analysis will be an invaluable textbook for statistics and medical students studying epidemiology, and a standard reference for practicing epidemiologists.
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.
A Modern Approach to Regression with R focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models.
An Introduction to Modern Econometrics Using Stata, by Christopher F. Baum, successfully bridges the gap between learning econometrics and learning how to use Stata. The book presents a contemporary approach to econometrics, emphasizing the role of method-of-moments estimators, hypothesis testing, and specification analysis while providing practical examples showing how the theory is applied to real datasets by using Stata.
