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An R Companion to Political Analysis
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List of Boxes and Figures Preface A Quick Reference Guide to R Companion Functions Introduction: Getting Acquainted with R About R Installing R A Quick Tour of the R Environment Objects Functions Getting Help Exercises Chapter 1: The R Companion Package Running Scripts Ten Tips for Writing Good R Scripts Managing R Output: Graphics and Text Additional Software for Working with R Debugging R Code Exercises Chapter 2: Descriptive Statistics Interpreting Measures of Central Tendency and Variation Describing Nominal Variables Describing Ordinal Variables Describing the Central Tendency of Interval Variables Describing the Dispersion of Interval Variables Obtaining Case-Level Information Exercises Chapter 3: Transforming Variables Applying Mathematical and Logical Operators to Variables Creating Indicator Variables Changing Variable Classes Adding or Modifying Variable Labels Collapsing Variables into Simplified Categories Centering or Standardizing a Numeric Variable Creating an Additive Index Exercises Chapter 4: Making Comparisons Cross-Tabulations and Mosaic Plots Line Charts Mean Comparison Analysis Box Plots Strip Charts Exercises Chapter 5: Making Controlled Comparisons Cross-Tabulation Analysis with a Control Variable Multiple Line Charts The legend Function Mean Comparison Analysis with a Control Variable Exercises Chapter 6: Making Inferences about Sample Means Finding the 95 Percent Confidence Interval of the Population Mean Testing Hypothetical Claims about the Population Mean Making Inferences about Two Sample Means Making Inferences about Two Sample Proportions Exercises Chapter 7: Chi-Square and Measures of Association Analyzing an Ordinal-Level Relationship Analyzing an Ordinal-Level Relationship with a Control Variable Analyzing a Nominal-Level Relationship with a Control Variable Exercises Chapter 8: Correlation and Linear Regression Correlation Analysis Bivariate Regression with a Dummy Variable Bivariate Regression with an Interval-Level Independent Variable Multiple Regression Analysis Multiple Regression with Ordinal or Categorical Variables Weighted Regression with a Dummy Variable Multiple Regression Analysis with Weighted Data Weighted Regression with Ordinal or Categorical Independent Variables Creating Tables of Regression Results Exercises Chapter 9: Visualizing Correlation and Regression Analysis Visualizing Correlation General Comments about Visualizing Regression Results Plotting Multiple Regression Results Interaction Effects in Multiple Regression Visualizing Regression Results with Weighted Data Special Issues When Plotting Observations with Limited Unique Values Exercises Chapter 10: Logistic Regression Thinking about Odds, Logged Odds, and Probabilities Estimating Logistic Regression Models Interpreting Logistic Regression Results with Odds Ratios Visualizing Results with Predicted Probabilities Curves Probability Profiles for Discrete Cases Model Fit Statistics for Logistic Regressions An Additional Example of Multivariable Logistic Regression Exercises Chapter 11: Doing Your Own Political Analysis Seven Doable Ideas Importing Data Writing It Up Appendix Table A.1 Alphabetical List of Variables in the GSS Dataset Table A.2 Alphabetical List of Variables in the NES Dataset Table A.3 Alphabetical List of Variables in the States Dataset Table A.4 Alphabetical List of Variables in the World Dataset About the Authors

Philip H. Pollock III is professor of political science at the University of Central Florida. He has taught courses in research methods at the undergraduate and graduate levels for nearly 40 years. His main research interests are American public opinion, voting behavior, techniques of quantitative analysis, and the scholarship of teaching and learning. His recent research has been on the effectiveness of Internet-based instruction. Pollock's research has appeared in the American Journal of Political Science, Social Science Quarterly, and British Journal of Political Science. Recent scholarly publications include articles in Political Research Quarterly, the Journal of Political Science Education, and PS: Political Science and Politics. Barry C. Edwards is a lecturer in the Department of Political Science at the University of Central Florida. He received his B.A. from Stanford University, a J.D. from New York University, and a Ph.D. from the University of Georgia. His teaching and research interests include American politics, law, and research methods. He founded the Political Science Data Group and created the PoliSciData.com web site. His research has been published in American Politics Research, Congress & the Presidency, Election Law Journal, Emory Law Journal, Georgia Bar Journal, Harvard Negotiation Law Review, Journal of Politics, Political Research Quarterly, Presidential Studies Quarterly, Public Management Review, and State Politics and Policy Quarterly.

#### Reviews

"R and its application continues to expand worldwide, replacing both its less flexible and less available alternatives and offering new opportunities. R Companion helps quickly climb the frequently steep learning curve of the 'program library of program libraries'. The book has a deserved good record as a path-breaker in teaching R with concerns towards political analysis. Highly recommended." -- Pertti Ahonen
"Phillip H. Pollock has written a timely, useful, and well-written book to accompany his popular text The Essentials of Political Analysis. The use of R in the classroom is increasing each year, and the need for user-friendly books to help integrate methodological training with this powerful statistical language has reached a critical stage. Professor Pollock's book fills this gap superbly. It takes the student from the elements of installing R on their own computer or laptop through the use of R to solve both simple and complex problems in social and political analysis. Students will love this book, as will their teachers." -- Courtney Brown