A Visual Guide to Stata Graphics, Second Edition, by Michael N. Mitchell, is a complete guide to Stata’s graph command and the associated Graph Editor. Whether you want to tame the Stata graph command, quickly find out how to produce a graphical effect, master the Stata Graph Editor, or learn approaches that can be used to construct custom graphs, this is the book to read.

An Introduction to Survival Analysis Using Stata, Second Edition, by Mario Cleves, William W. Gould, Roberto G. Gutierrez, and Yulia Marchenko, is the ideal tutorial for professional data analysts who want to learn survival analysis for the first time or who are well versed in survival analysis but not as dexterous in using Stata to analyze survival data.

Multilevel and Longitudinal Modeling Using Stata, 2nd Edition, by Sophia Rabe-Hesketh and Anders Skrondal, looks specifically at Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are “mixed” because they allow fixed and random effects, and they are “generalized” because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables.

Generalized Linear Models and Extensions, 2nd Edition, by James Hardin and Joseph Hilbe, thoroughly covers GLMs, both theoretically and computationally. After presenting general theory, the text then breaks down each distribution. The final part of the text concerns extensions of GLMs, and includes many examples using the authors’ own Stata programs and Stata’s official glm command.

Regression Models for Categorical Dependent Variables Using Stata, 2nd Edition, by J. Scott Long and Jeremy Freese, shows how to use Stata to fit and interpret regression models for categorical data. Nearly 50% longer than the previous edition, the second edition covers new topics for fitting and interpreting models included in Stata 9, such as multinomial probit models, the stereotype logistic model, and zero-truncated count models. Many of the interpretation techniques have been updated to include interval and point estimates.

An Introduction to Stata for Health Researchers, by Svend Juul, provides in-depth and insightful coverage of all three topics for which Stata is known: data management, statistics, and graphics. By focusing on those who are involved in health research, Juul is able to strongly cover each topic.

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.

Maximum Likelihood Estimation with Stata, 3rd Edition, is written for researchers in all disciplines who need to fit models using maximum likelihood estimation. This edition offers a wealth of material about the ml command, updated to include new features introduced in Stata 9.

Data Analysis Using Stata, provides a comprehensive introduction to Stata that will be useful to those who are just learning statistics and Stata, as well as to users of other statistical packages making the switch to Stata. Throughout the book, the authors make extensive use of examples using data from the German Socioeconomic Panel, a large survey of households containing demographic, income, employment, and other key information.

Thirty-three Stata Tips; Since 2003, the Stata Journal has published Stata Tips on special issues in data analysis with Stata. Now Thirty-three Stata Tips compiles these useful guides into a compact tome for ease of reference. In keeping with the Stata spirit, Tips are from Stata users and StataCorp employees alike and will serve as guideposts for both new and experienced users.

Modern Epidemiology, Third Edition, by Kenneth J. Rothman, Sander Greenland, and Timothy L. Lash, provides a complete desk reference of the methods of modern epidemiology, with contributions from the three authors plus nineteen leading experts from various subfields.

Introductory Econometrics: A Modern Approach, 4th Edition ives up to its subtitle. This text exemplifies a modern approach to econometrics in its choice of topics and its treatment of standard material.

Applied Econometrics for Health Economists, 2nd Edition, by Andrew Jones intuitively discusses the major methods used in applied health economics. In each discussion, Jones uses Stata to analyze real data and interprets the results.

Event History Analysis with Stata, by Hans-Peter Blossfeld, Katrin Golsch, and Gotz Rohwer, presents survival analysis from a social science perspective and covers both basic and advanced topics. The authors give examples throughout using Stata (version 9) and data from the German Life History Study.

Applied Health Economics, by Andrew Jones, Nigel Rice, Teresa Bago d’Uva, and Silvia Balia, shows how to summarize and analyze health-economic 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 through application.

Epidemiology: Study Design and Data Analysis, 2nd Edition, by Mark Woodward, is ideal for researchers who need statistical solutions to epidemiology problems and statisticians who wish to learn how their science applies to epidemiology.