3rd Edition

# Data Analysis Using Stata, Third Edition

By Ulrich Kohler, Frauke Kreuter Copyright 2012
497 Pages 22 B/W Illustrations
by Stata Press

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
Do-files
Exiting Stata

Working with Do-Files
From interactive work to working with a do-file
Designing do-files

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

Regression Models for Categorical Dependent Variables
The linear probability model
Basic concepts
Logistic regression with Stata
Logistic regression diagnostics
Likelihood-ratio test
Refined models

The goal: The data matrix
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