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A Stata® Companion to Political Analysis

A Stata® Companion to Political Analysis

Fourth Edition
Experience with SAGE edge

October 2018 | 288 pages | CQ Press

“This textbook is a great resource for teaching students how to conduct basic quantitative analysis using Stata. It provides intuitive examples from real data sets. I think it is a great resource for teaching students how to carry their own research projects.”
—Sabri Ciftci, Kansas State University

Popular for its speed, flexibility, and attractive graphics, Stata is a powerful tool for political science students. With Philip Pollock's Fourth Edition of A Stata® Companion to Political Analysis, students quickly learn Stata via step-by-step instruction, more than 50 exercises, customized datasets, annotated screen shots, boxes that highlight Stata's special capabilities, and guidance on using Stata to read raw data. This attractive and value-priced workbook, an ideal complement to Pollock’s Essentials of Political Analysis, is a must-have for any political science student working with Stata.

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Figures and Tables
Introduction: Getting Started
About Companion Datasets  
Chapter 1 Introduction to Stata
Information About a Dataset  
Information About Variables  
General Syntax of Stata Commands  
Printing Results and Copying Output  
Log Files  
Getting Help  
Customizing Your Display  
Chapter 2 Descriptive Statistics
Interpreting Measures of Central Tendency and Variation  
Describing Nominal Variables  
A CLOSER LOOK: Weighting the GSS and NES Datasets  
Describing Ordinal Variables  
Describing Interval Variables  
Bar Charts for Nominal and Ordinal Variables  
A CLOSER LOOK: Stata’s Graphics Editor  
Histograms for Interval Variables  
Obtaining Case-Level Information With sort and list  
Chapter 3 Transforming Variables
Creating Indicator Variables  
Working With Variable Labels  
Collapsing Variables Into Simplified Categories  
Centering or Standardizing a Numeric Variable  
Creating an Additive Index  
Chapter 4 Making Comparisons
Cross-Tabulation Analysis  
Visualizing Comparisons With Nominal or Ordinal Dependent Variables  
A CLOSER LOOK: The replace Command  
Mean Comparison Analysis  
A CLOSER LOOK: The format Command  
Visualizing Comparisons With Interval-Level Dependent Variables  
Strip Charts: Graphs for Small-N Datasets  
Chapter 5 Making Controlled Comparisons
Cross-Tabulation Analysis With a Control Variable  
A CLOSER LOOK: The “If ” Qualifier  
Visualizing Controlled Comparisons With Categorical Dependent Variables  
Mean Comparison Analysis With a Control Variable  
Visualizing Controlled Mean Comparisons  
Chapter 6 Making Inferences About Sample Means
Finding the 95 Percent Confidence Interval of a Sample Mean  
Testing a Hypothetical Claim About the Population Mean  
Testing the Difference Between Two Sample Means  
A CLOSER LOOK: Inferences About Means With Unweighted Data  
Extending the mean and lincom Commands to Other Situations  
Making Inferences About Sample Proportions  
A CLOSER LOOK: Inferences About Proportions With Unweighted Data  
Chapter 7 Chi-Square and Measures of Association
Analyzing Ordinal-Level Relationships  
A CLOSER LOOK: Analyzing Unweighted Data With The tabulate Command  
Analyzing an Ordinal-Level Relationship With a Control Variable  
Analyzing Nominal-Level Relationships  
Chapter 8 Correlation and Linear Regression
Correlation Analysis  
Regression Analysis  
A CLOSER LOOK: Treating Census as a Sample  
A CLOSER LOOK: R-Squared and Adjusted R-Squared: What’s the Difference?  
Creating a Scatterplot With a Linear Prediction Line  
Multiple Regression  
A CLOSER LOOK: Bubble Plots  
Correlation and Regression Analysis With Weighted Data  
Chapter 9 Dummy Variables and Interaction Effects
Regression With Multiple Dummy Variables  
Interaction Effects in Multiple Regression  
Graphing Linear Prediction Lines for Interaction Relationships  
Changing the Reference Category  
Chapter 10 Logistic Regression
Thinking About Odds, Logged Odds, and Probabilities  
Estimating Logistic Regression Models  
Logistic Regression With Multiple Independent Variables  
A CLOSER LOOK: Comparing Logistic Regression Models With the estimates and lrtest Commands  
Graphing Predicted Probabilities With One Independent Variable  
Graphing Predicted Probabilities With Multiple Independent Variables  
Chapter 11 Doing Your Own Political Analysis
Seven Doable Ideas  
Importing Data Into Stata  
Writing It Up  
Table A-1: Variables in the GSS Dataset in Alphabetical Order  
Table A-2: Variables in the NES Dataset in Alphabetical Order  
Table A-3: Variables in the States Dataset by Topic  
Table A-4: Variables in the World Dataset by Topic  

“An excellent companion for statistical computing using Stata that is a must-use for those instructors that assign the Pollock text and use Stata in their course."

Donald Gooch
Stephen F. Austin State University

“This textbook is a great resource for teaching students how to conduct basic quantitative analysis using Stata. It provides intuitive examples from real data sets. I think it is a great resource for teaching students how to carry their own research projects.”

Sabri Ciftci
Kansas State University

“This is a great workbook to teach Stata to students who are also learning the basics of statistical analysis. It comes with four datasets that can be used to run analyses. Its exercises are very useful and the instructor tools are great.”

Tijen Demirel-Pegg
Indiana University – Purdue University Indianapolis

“For teaching Stata to undergraduates, this book provides the friendliest approach I have found. Over six straight semesters of teaching the same course, I have found it to make both my teaching experience and the students’ learning experience far more interesting and interactive than a typical “Research Methods” course. It provides exceptional instructional assistance, and presents information to students in an easily digestible way.”

Lilliana Mason, Rutgers
The State University of New Jersey
Key features


  • Updated companion datasets (2016 ANES and 2016 GSS) provide instructors with opportunities to apply research methods to current issues, like the 2016 election, LGBTQ+ politics, inequality, and immigration.
  • Examples drawn from all subfields of political science give instructors with different substantive interests (i.e. comparative politics, international relations, law and courts) a variety of  examples to use in their class.
  • Updated chapter exercises with Instructor's Solution Manual make grading easier and includes the commands used to solve chapter exercises.
  • SAGE edge provides students helpful tools, including eFlashcards, practice quizzes, and more, in one easy-to-use online environment. 



  • Detailed instruction on how to conduct political analysis helps students become competent using the Stata program. 
  • Four customized datasets give students opportunities to practice writing commands and analyzing results. 
  • Over 50 exercises reinforce important concepts and support their application. 

Sample Materials & Chapters

Chapter 1: Introduction to Stata

Chapter 4: Making Comparisons

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