Statistics with Stata: Version 12, Eighth Edition

by Lawrence C. Hamilton

Statistics with Stata: Version 12 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.

The first three chapters cover getting started in Stata, data manipulation, and graphics. Hamilton then introduces many statistical procedures available within Stata. These include summary statistics and tables, ANOVA, linear regression (and diagnostics), robust methods, nonlinear regression, regression models for limited dependent variables, complex survey data, survival analysis, factor analysis, cluster analysis, structural equation modeling, multiple imputation, time series, and multilevel mixed-effects models. The final chapter provides an introduction to programming.

The organization of this book makes it ideal for those who are new to statistics, experienced statisticians who are new to Stata, and Stata users wishing to explore Stata's capabilities in a new field. A series of example commands with brief descriptions at the beginning of each chapter demonstrates the Stata syntax for topics discussed in the chapter. For those already familiar with the statistical technique but not with the corresponding Stata commands, this example section may be all that is needed to begin an analysis using Stata. Following the example sections, Hamilton addresses each topic in more detail with descriptions of statistical procedures, examples using real data, and interpretation of the Stata output.
 

Table of contents

Preface

Notes on the Eighth Edition
Acknowledgments

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 by Typing in Data

 Creating a New Dataset by Copy and Paste
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
Collapsing Data
Reshaping Data
Using Weights
Creating Random Data and Random Samples
Writing Programs for Data Management

3 Graphs

Example Commands
Histograms
Box Plots

Scatterplots and Overlays
Line Plots and Connected-Line Plots
Other Twoway Plot Types
Bar Charts and Pie Charts
Symmetry and Quantile Plots
Adding Text to Graphs
Graphing with Do-Files
Retrieving and Combining Graphs
Graph Editor
Creative Graphing

4 Survey Data

          Example Commands
          Declare Survey Data
          Design Weights
          Poststratification Weights
          Survey-Weighted Tables and Graphs
          Bar Charts for Multiple Comparisons 

5 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

6 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
Factor Variables and Analysis of Covariance (ANCOVA)
Predicted Values and Error-Bar Charts

7 Linear Regression Analysis

Example Commands
Simple Regression
Correlation
Multiple Regression
Hypothesis Tests
Dummy Variables
Interaction Effects
Robust Estimates of Variance
Predicted Values and Residuals
Other Case Statistics
Diagnosing Multicollinearity and Heteroskedasticity
Confidence Bands in Simple Regression
Diagnostic Graphs

8 Advanced Regression Methods 

Example Commands
Lowess Smoothing
Robust Regression
Further rreg and qreg Applications
Nonlinear Regression — 1
Nonlinear Regression — 2
Box–Cox Regression
Multiple Imputation of Missing Values
Structural Equation Modeling

 9 Logistic Regression 

Example Commands

Space Shuttle Data

Using Logistic Regression

Marginal or Conditional Effects Plots 

Diagnostic Statistics and Plots

Logistic Regression with Ordered-Category y

Multinomial Logistic Regression

          Multiple Imputation of Missing Values — Logit Regression Example

10 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

11 Principal Components, Factor, and Cluster Analysis

Example Commands

Principal Component Analysis and Principal Component Factoring 

Rotation

Factor Scores

Principal Factoring

Maximum-Likelihood Factoring

Cluster Analysis — 1

Cluster Analysis — 2

          Using Factor Scores in Regression
          Measurement and Structural Equation Models

12 Time Series Analysis

Example Commands

Smoothing

Further Time Plot Examples

          Recent Climate Change

Lags, Leads, and Differences

Correlograms

ARIMA Models

          ARMAX Models

Dataset Sources

References

Index

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