A Stata Companion to Political Analysis, Third Edtition

by Philip H. Pollock III

The third edition of Philip Pollock’s A Stata Companion to Political Analysis is an excellent guide, whether you are taking your first political-science course or teaching one. The new edition was written using Stata 13, but the datasets can be read with Stata 11 through 13. Like the previous editions, the book maintains the same instructional insights and focus on how to present results effectively.

Each chapter is a tutorial with a rich set of exercises. The book surveys the statistical methods that professional political scientists use; the treatment of research methods deftly incorporates data management, graphical analysis, and statistics into the political-science domain. In this edition, the author emphasizes the use of do-files as a unified way of working with Stata. Also, the author complements the content of the previous edition by illustrating the benefits of the margins and marginsplot commands as tools to use and interpret results after estimation. He also discusses the topic of weighted and unweighted data. The thorough examples show how to complete each task with Stata while giving firsthand experience in political research.

Table of contents

1. Introduction to Stata

Information about a Dataset
Information about Variables
Do-Files
Log Files
Printing Results and Copying Output
A CLOSER LOOK: Weighting the gss2012 and nes2012 Datasets
Getting Help
Exercises
Notes

2. Descriptive Statistics

Interpreting Measures of Central Tendency and Variation
Describing Nominal Variables
Describing Ordinal Variables
Describing Interval Variables
Obtaining Bar Charts and Histograms
Obtaining Case-Level Information with sort and list
Exercises
Notes

3. Transforming Variables

Transforming Categorical Variables
Transforming Interval Variables
A CLOSER LOOK: The xtile Command
The label define and label values Commands
Creating an Additive Index
Creating Indicator Variables
Exercises
Notes

4. Making Comparisons

5. Making Controlled Comparisons

6. Making Inferences about Sample Means

Describing a Sample Mean
Testing the Difference between Two Sample Means
Extending the mean and lincom Commands
Exercises
Notes

7. Chi-square and Measures of Association

Analyzing Ordinal-Level Relationships

Summary

Analyzing an Ordinal-Level Relationship with a Control Variable
Analyzing Nominal-Level Relationships
Analyzing Unweighted Data with the tabulate Command
Exercises
Notes

8. Correlation and Linear Regression

The correlate Command and the regress Command
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 with Weighted Data
Exercises
Notes

9. Dummy Variables and Interaction Effects

Regression with Dummy Variables
A CLOSER LOOK: The test Command
Interaction Effects in Multiple Regression
Graphing Linear Prediction Lines for Interaction Relationships
Exercises
Notes

10. Logistic Regression

The logit Command and the logistic Command
Logistic Regression with Multiple Independent Variables
A CLOSER LOOK: The estimates Command and the lrtest Command
Working with Predicted Probabilities

The margins Command with the atmeans Option
The margins Command with the over Option

MERS-MEMS Hybrids
Exercises
Notes

Five Doable Ideas

Political Knowledge
Economic Performance and Election Outcomes
State Courts and Criminal Procedure
Electoral Turnout in Comparative Perspective
Congress

Inputting Data

Stata Formatted Datasets
Microsoft Excel Datasets

Writing It Up

The Research Question
Previous Research
Data, Hypotheses, and Analysis
Conclusions and Implications

Notes

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