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
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.
Microeconometrics Using Stata, by A. Colin Cameron and Pravin K. Trivedi, is an outstanding introduction to microeconometrics and how to do microeconometric research using Stata. Aimed at students and researchers, this book covers topics left out of microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata.
The common ground at the interface between statistics and econometrics is of considerable importance for researchers, practitioners, and students of both subjects, and it is also of direct interest to those working in other areas of applied sciences
Applied Econometrics with R by Kleiber and Zeileis is a welcome and timely addition to the fast-growing Use R! series of R titles published by Springer. As noted by the authors, this appears to be the rst book1 that focusses on R and econometrics. Researchers in quantitative social sciences in general, and econometrics in particular, have often favoured scripting languages such as GAUSS or Stata, or packages such as EViews.
