Statistics with Stata (Updated for Version 10)

by Lawrence C. Hamilton

 Statistics with Stata (Updated for Version 10) is the latest edition in Professor Lawrence C. Hamilton’s popular Statistics with Stata series. Intended to bridge the gap between statistical texts and Stata’s own documentation, Statistics with Stata demonstrates how to use Stata to perform a variety of tasks. This text is ideal as a self-study course for those new to statistics or those migrating from other statistical software to Stata and as a valuable reference for experienced Stata users wishing to explore Stata’s capabilities in fields new to them.

Hamilton covers topics including getting started in Stata, data manipulation, graphics, summary statistics and tables, ANOVA, linear regression (and diagnostics), curve fitting, robust methods, regression models for limited dependent variables, panel (longitudinal) data and mixed models, survey data, survival analysis, factor analysis, cluster analysis, time series, and an introduction to programming.

Notable changes to Statistics with Stata (Updated for Version 10) include a new chapter on survey data analysis using Stata’s svy: prefix command and a chapter on the multilevel and mixed model commands introduced in Stata 10. Chapter 3, covering graphics, has been updated to include a section demonstrating Stata’s Graph Editor. The entire book has also been updated to reflect changes in output, syntax, and features.

Table of contents

Preface

1 Stata and Stata Resources

A Typographical Note

An Example Stata Session

Stata's Documentation and Help Files

Searching for Information

StataCorp

Statalist

The Stata Journal

Books Using Stata

2 Data Management

Example Commands
Creating a New Dataset
Specifying Subsets of the Data: in and if Qualifiers
Generating and Replacing Variables
Missing Value Codes
Using Functions
Converting between Numeric and String Formats
Creating New Categorical and Ordinal Variables
Using Explicit Subscripts with Variables
Importing Data from Other Programs
Combining Two or More Stata Files
Transposing, Reshaping, or Collapsing Data
Using Weights
Creating Random Data and Random Samples
Writing Programs for Data Management
Managing Memory

3 Graphs

Example Commands
Histograms
Scatterplots
Line Plots
Connected-Line Plots
Other Twoway Plot Types
Box Plots
Pie Charts
Bar Charts
Dot Plots
Symmetry and Quantile Plots
Adding Text to Graphs
Overlaying Multiple Twoway Plots
Graphing with Do-Files
Retrieving and Combining Graphs
Graph Editor
Creative Graphing

4 Summary Statistics and Tables

Example Commands
Summary Statistics for Measurement Variables
Exploratory Data Analysis
Normality Tests and Transformations
Frequency Tables and Two-Way Cross-Tabulations
Multiple Tables and Multi-Way Cross-Tabulations
Tables of Means, Medians, and Other Summary Statistics
Using Frequency Weights

5 ANOVA and Other Comparison Methods

Example Commands
One-Sample Tests
Two-Sample Tests
One-Way Analysis of Variance (ANOVA)
Two- and N-Way Analysis of Variance
Analysis of Covariance (ANCOVA)
Predicted Values and Error-Bar Charts

6 Linear Regression Analysis

Example Commands
The Regression Table
Multiple Regression
Predicted Values and Residuals
Basic Graphs for Regression
Correlations
Hypothesis Tests
Dummy Variables
Automatic Categorical-Variable Indicators and Interactions
Stepwise Regression
Polynomial Regression

7 Regression Diagnostics

Example Commands

SAT Score Regression, Revisited

Diagnostic Plots

Diagnostic Case Statistics

Multicollinearity

8 Fitting Curves

Example Commands

Band Regression

Lowess Smoothing

Regression with Transformed Variables — 1

Regression with Transformed Variables — 2

Conditional Effect Plots

Nonlinear Regression — 1

Nonlinear Regression — 2

9 Robust Regression

Example Commands

Regression with Ideal Data

Y Outliers

X Outliers (Leverage)

Asymmetrical Error Distributions

Robust Analysis of Variance

Further rreg and qreg Applications

Robust Estimates of Variance — 1

Robust Estimates of Variance — 2

10 Logistic Regression

Example Commands

Space Shuttle Data

Using Logistic Regression

Conditional Effect Plots

Diagnostic Statistics and Plots

Logistic Regression with Ordered-Category y

Multinomial Logistic Regression

11 Survival and Event-Count Models

Example Commands

Survival-Time Data

Count-Time Data

Kaplan–Meier Survivor Functions

Cox Proportional Hazard Models

Exponential and Weibull Regression

Poisson Regression

Generalized Linear Models

12 Principal Components, Factor, and Cluster Analysis

Example Commands

Principal Components

Rotation

Factor Scores

Principal Factoring

Maximum-Likelihood Factoring

Cluster Analysis — 1

Cluster Analysis — 2

13 Time Series Analysis

Example Commands

Smoothing

Further Time Plot Examples

Lags, Leads, and Differences

Correlograms

ARIMA Models

          ARMAX Models

14 Survey Data Analysis 

Example Commands
Probability Weights
Poststratification Weights
Declare Survey Data
Survey-Weighted Tables and Graphs
Regression-Type Modeling
Conditional Effect Plots for Interactions
Other Tools for Survey Analysis

References

Index