Search
   >> Home >> Bookstore >> Social science >> A Stata Companion to Political Analysis, Second Edition

A Stata Companion to Political Analysis, Second Edition

Author:
Philip H. Pollock III
Publisher: CQ Press
Copyright: 2010
ISBN-13: 978-1-60871-671-5
Pages: 237; paperback
Price: $49.75

Comment from the Stata technical group

The second edition of Philip Pollock’s A Stata Companion to Political Analysis can guide you whether you are taking your first political-science course or teaching one. The new edition has been updated for Stata 10 and Stata 11 and makes extensive use of the Graph Editor. Also new are line graphs, which are often clearer and more effective than bar graphs.

Each chapter is a tutorial with a rich set of exercises. The tutorials will teach you how to control Stata with either the command line or the graphical user interface—whichever mode fits the task. The book also 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. The thorough examples show how to complete each task with Stata while giving firsthand experience in political research.


Table of contents

Figures
Preface
Getting Started
Dataset CD
Notes
Chapter 1 Introduction to Stata
Commands Covered: describe; codebook varname; set more off; File → Log → Begin; search keyword; help command_name; which package_name; ssc install package_name
Obtaining Information about a Dataset
Obtaining Information about Variables
Creating and Viewing a Log File
Printing Results and Copying Output
Getting Help
Installing Statistical Modules
Exercises
Notes
Chapter 2 Descriptive Statistics
Commands Covered: tabulate varname; summarize varname, detail; sktest varname; histogram varname, d percent; histogram varname, percent; sort varname; list varname; The Graph Editor Recorder
Interpreting Measures of Central Tendency and Variation
Describing Nominal Variables
Describing Ordinal Variables
Describing Interval Variables
Obtaining Bar Charts and Histograms
Creating Bar Charts
A Closer Look: Graph Editor Recorder
Creating Histograms
Obtaining Case-level Information with sort and list
Exercises
Notes
Chapter 3 Transforming Variables
Commands Covered: recode, generate(); generate, recode(); xtile, nquantiles(); generate; tabulate, generate(); label variable; label define; label values; drop; aorder
A Workbook Convention: Weighting the nes2008 Dataset
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
Chapter 4 Making Comparisons
Commands Covered: tabulate dep_var indep_var, column; tabulate indep_var, summarize (dep_var); format; _gwtmean, dep_var_mean=dep_var [if], by (indep_var); if; twoway (line dep_var indep_var, sort); replace; graph bar (mean) dep_var, over (indep_var)
Cross-tabulation Analysis
Mean Comparison Analysis
Visualizing Relationships with Line Charts and Bar Charts
A Closer Look: The format Command
Graphing an Interval-level Dependent Variable
A Closer Look: The if Qualifier
Graphing a Categorical Dependent Variable
A Closer Look: The replace Command
Exercises
Notes
Chapter 5 Making Controlled Comparisons
Commands Covered: bysort cntrl_var: tabulate dep_var indep_var, col; tabulate cntrl_var indep_var, summarize (dep_var); graph bar dep_var, over (cntrl_var) over (indep_var); twoway (line dep_var indep_var if cntrl_var==value1, sort) (line dep_var indep_var if cntrl_var==value2, sort)
Cross-tabulation Analysis with a Control Variable
Bar Charts for Controlled Comparisons with a Categorical Dependent Variable
Mean Comparison Analysis with a Control Variable
Line Charts for Controlled Comparisons with an Interval-level Dependent Variable
Exercises
Notes
Chapter 6 Making Inferences about Sample Means
Commands Covered: ttest varname = testvalue; ttest varname, by(group_var); robvar varname, by(group_var)
Describing a Sample Mean
Testing the Difference Between Two Sample Means
Exercises
Notes
Chapter 7 Chi-square and Measures of Association
Commands Covered: (tabulate option) chi2; (tabulate option) V; somersd indep_var dep_var; lambda dep_var indep_var
Analyzing Ordinal-level Relationships
Analyzing Nominal-level Relationships
A Problem with Lambda
Exercises
Notes
Chapter 8 Correlation and Linear Regression
Commands Covered: correlate varlist; regress dep_var indep_var(s); twoway (scatter dep_var indep_var) (lfit dep_var indep_var)
A Closer Look: R-squared and Adjusted R-squared: What’s the Difference?
Creating a Scatterplot with a Linear Prediction Line
Exploring Multivariate Relationships with Regression
Exercises
Notes
Chapter 9 Dummy Variables and Interaction Effects
Commands Covered: xi: regression dep_var i.indep_var; char varname [omit] #; test varname1 = varname2; predict newvar
Regression with Dummy Variables
A Closer Look: The test Command
Interaction Effects in Multiple Regression
Graphing Linear Prediction Lines for Interaction Relationships
Exercises
Notes
Chapter 10 Logistic Regression
Commands Covered: logit dep_var indep_var(s); logistic dep_var indep_var(s), [coef]; estimates store name; lrtest name, force; adjust indep_var1, by(indep_var2) pr gen(newvar); quietly; tabstat dep_var1 dep_var2, by(indep_var)
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: Models with One Independent Variable
Working with Predicted Probabilities: Models with Multiple Independent Variables
Exercises
Notes
Chapter 11 Doing Your Own Political Analysis
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
PDF Format or Hand-coded Data
Writing It Up
The Research Question
Previous Research
Data, Hypotheses, and Analysis
Conclusions and Implications
Notes
Appendix
Table A-1: Descriptions of Constructed Variables in gss2006
Table A-2: Descriptions of Variables in the states Dataset
Table A-3: Descriptions of Variables in the world Dataset
The Stata Blog: Not Elsewhere Classified Find us on Facebook Follow us on Twitter LinkedIn Google+ Watch us on YouTube