Books published by Stata Press

This book presents a broad range of applied econometric techniques for environmental econometrics and illustrating how they can be applied in Stata.

Using illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis. Rather than focus on clusters of commands, it takes a modular approach that enables readers to quickly identify and implement the necessary task without having to access background information first.

Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. This text thoroughly covers GLMs, both theoretically and computationally, with an emphasis on Stata. The theory consists of showing how the various GLMs are special cases of the exponential family.

Over the past several decades, item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral, educational, social, business, marketing, clinical, and health sciences.

Survey Weights: A Step-by-Step Guide to Calculation is the first guide geared towards Stata users that systematically covers the major steps taken in creating survey weights. These weights are used to project a sample to some larger population and can be computed for either probability or nonprobability samples.

This book provides an excellent overview of the methods used to analyze data on healthcare expenditure and use. It introduces readers to widely used methods, shows them how to perform these methods in Stata, and illustrates how to interpret the results.

An Introduction to Survival Analysis Using Stata, Revised Third Edition 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 are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Statäs survival analysis routines.This revised third edition has been updated for Stata 14, and it includes a new section on predictive margins and marginal effects, which demonstrates how to obtain and visualize marginal predictions and marginal effects using the margins and marginsplot commands after survival regression models.

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Statäs data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian perspective and covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of results.

Speaking Stata Graphics is ideal for researchers who want to produce effective, publication-quality graphs. A compilation of articles from the popular Speaking Stata column by Nicholas J. Cox, this book provides valuable insights about Stata's built-in and user-written statistical-graphics commands.

Through real-world case studies, this book shows how to use Stata to estimate a class of flexible parametric survival models. It discusses the modeling of time-dependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a particular disease when the cause of death has not been recorded. The book describes simple quantification of differences between any two covariate patterns through calculation of time-dependent hazard ratios, hazard differences, and survival differences.

This practical guide explores all the features of Statäs sem command. This revised edition includes output, syntax, and instructions for fitting models with the Stata 13 SEM Builder. It shows how this graphical interface allows users to draw publication-quality path diagrams and fit the models without writing any programming code. Each model is presented along with the necessary Stata code. The datasets used are available for download online.