This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats, the ability to write highly customized Excel files, the ability to have multiple Stata datasets open at once, and the ability to store and manipulate string variables stored as Unicode. Further, this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition, the chapters are organized by data management areas: reading and writing datasets, cleaning data, labeling datasets, creating variables, combining datasets, processing observations across subgroups, changing the shape of datasets, and programming for data management. Within each chapter, each section is a self-contained lesson illustrating a particular data management task (for instance, creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the "nuts and bolts" examples, author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management, while experienced users will find this information to be handy and time saving--there is a good chance that even the experienced user will learn some new tricks.

Where do I start? How do I know if I’m asking the right questions? How do I analyze the data once I have it? How do I report the results? When will I ever understand the process? If you are new to using the Stata software, and concerned about applying it to a project, help is at hand. David Pevalin and Karen Robson offer you a step by step introduction to the basics of the software, before gently helping you develop a more sophisticated understanding of Stata and its capabilities. The book will guide you through the research process offering further reading where more complex decisions need to be made and giving 'real world' examples from a wide range of disciplines and anecdotes that clarify issues for readers. The book will help with: Manipulating and organizing data Generating statistics Interpreting results Presenting outputs The Stata Survival Manual is a lifesaver for both students and professionals who are using the Stata software!

Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.

The Mata Book: A Book for Serious Programmers and Those Who Want to Be is the book that Stata programmers have been waiting for. Mata is a serious programming language for developing small- and large-scale projects and for adding features to Stata. What makes Mata serious is that it provides structures, classes, and pointers along with matrix capabilities. The book is serious in that it covers those advanced features, and teaches them. The reader is assumed to have programming experience, but only some programming experience. That experience could be with Stata's ado language, or with Python, Java, C++, Fortran, or other languages like them. As the book says, "being serious is a matter of attitude, not current skill level or knowledge". The author of the book is William Gould, who is also the designer and original programmer of Mata, of Stata, and who also happens to be the president of StataCorp.

The Power of Stata Graphics at Your Fingertips Whether you are new to Stata graphics or a seasoned veteran, this book teaches you how to use Stata to make high-quality graphs that stand out and enhance statistical results. With over 900 illustrated examples and quick-reference tabs, it offers a guide to creating and customizing graphs for any type of statistical data using either Stata commands or the Graph Editor. The author displays each graph example in full color with simple and clear instructions. He shows how to produce various types of graph elements, including marker symbols, lines, legends, captions, titles, axis labels, and grid lines. Reflecting the new graphics features of Stata, this thoroughly updated and expanded edition contains a new chapter that explains how to exploit the power of the new Graph Editor. This edition also includes additional examples and illustrates nearly every example with the Graph Editor.

Designed to assist those working in health research, An Introduction to Stata for Health Researchers explains how to maximize the versatile Stata program for data management, statistical analysis, and graphics for research. The first nine chapters are devoted to becoming familiar with Stata and the essentials of effective data management. The text is also a valuable companion reference for more advanced users. It covers a host of useful applications for health researchers including the analysis of stratified data via epitab and regression models; linear, logistic, and Poisson regression; survival analysis including Cox regression, standardized rates, and correlation/ROC analysis of measurements.

"[This book] provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves not only as a tutorial for those wishing to learn survival analysis but as a ... reference for experienced researchers ..."--Book jacket.