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cover Bayesian Analysis with Stata, by John Thompson, is a compendium of Stata user-written commands for Bayesian analysis. It contains just enough theoretical and foundational material to be useful to all levels of users interested in Bayesian statistics, from neophytes to aficionados.
cover Regression Models for Categorical Dependent Variables Using Stata, Third Edition, by J. Scott Long and Jeremy Freese, is an essential reference for those who use Stata to fit and interpret regression models for categorical data. Although regression models for categorical dependent variables are common, few texts explain how to interpret such models; this text decisively fills the void.
cover Introduction to Time Series Using Stata, by Sean Becketti, is a first-rate, example-based guide to time-series analysis and forecasting using Stata. It can serve as both a reference for practitioners and a supplemental textbook for students in applied statistics courses.
cover Discovering Structural Equation Modeling Using Stata, Revised Edition, by Alan C. Acock, successfully introduces both the statistical principles involved in structural equation modeling (SEM) and the use of Stata to fit these models. Acock demonstrates how to fit a wide variety of models that fall within the SEM framework and provides datasets that enable the reader to follow along with each example.
cover A Visual Guide to Stata Graphics, Third Edition, by Michael N. Mitchell, is a complete guide to Stata's graph and the associated Graph Editor. Whether you want to tame graph, 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.

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New series: Maria Gaetana Agnesi, James Durbin, Benjamin Gompertz, Leopold Kronecker, and Siméon-Denis Poisson.

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