Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks. The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand. Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.
The First Time Starting Stata Setting up your screen Your first analysis Do-files Exiting Stata Working with Do-Files From interactive work to working with a do-file Designing do-files Organizing your work The Grammar of Stata The elements of Stata commands Repeating similar commands Weights General Comments on the Statistical Commands Regular statistical commands Estimation commands Creating and Changing Variables The commands generate and replace Specialized recoding commands Recoding string variables Recoding date and time Setting missing values Labels Storage types, or the ghost in the machine Creating and Changing Graphs A primer on graph syntax Graph types Graph elements Multiple graphs Saving and printing graphs Describing and Comparing Distributions Categories: Few or many? Variables with few categories Variables with many categories Statistical Inference Random samples and sampling distributions Descriptive inference Causal inference Introduction to Linear Regression Simple linear regression Multiple regression Regression diagnostics Model extensions Reporting regression results Advanced techniques Regression Models for Categorical Dependent Variables The linear probability model Basic concepts Logistic regression with Stata Logistic regression diagnostics Likelihood-ratio test Refined models Advanced techniques Reading and Writing Data The goal: The data matrix Importing machine-readable data Inputting data Combining data Saving and exporting data Handling big datasets Do-Files for Advanced Users and User-Written Programs Two examples of usage Four programming tools User-written Stata commands Around Stata Resources and information Taking care of Stata Additional procedures References Author Index Subject Index Exercises appear at the end of each chapter.
