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Data Analysis Using Stata, Second Edition - By Ulrich Kohler and Frauke Kreuter

Comment from the Stata Technical group


Updated to include changes to Stata over the past several years, Data Analysis Using Stata, Second Edition comprehensively introduces Stata and will be useful to those who are just learning statistics and Stata, as well as to users of other statistical packages who are making the switch to Stata. Throughout the book, Kohler and Kreuter show examples using data from the German Socioeconomic Panel, a large survey of households containing demographic, income, employment, and other key information. The authors describe the Graph Editor and time-of-day variables, two features added in Stata 10, in this new edition.

Kohler and Kreuter’s book is a valuable introduction to Stata. The authors take a hands-on approach, leading you step by step through actual Stata sessions to answer practical questions commonly asked by social scientists.

They begin with an introduction to the Stata interface and then proceed with a description of Stata syntax and simple programming tools like foreach loops. The core of the book includes chapters on producing tables and graphs, performing linear regression, and using logistic regression. Kohler and Kreuter use multiple examples to illustrate all key concepts.

The rest of the book includes chapters on reading text files, writing programs and ado-files, and using Internet resources, such as the search command and the SSC archive.

Table of Contents

List of Tables

List of Figures

  1. "The first time"
    1.1 Starting Stata
    1.2 Setting up your screen
    1.3 Your first analysis
    1.3.1 Inputting commands
    1.3.2 Files and the working memory
    1.3.3 Loading data
    1.3.4 Variables and observations
    1.3.5 Looking at data
    1.3.6 Interrupting a command and repeating a command
    1.3.7 The variable list
    1.3.8 The in qualifier
    1.3.9 Summary statistics
    1.3.10 The if qualifier
    1.3.11 Define missing values
    1.3.12 The by prefix
    1.3.13 Command options
    1.3.14 Frequency tables
    1.3.15 Variable labels and value labels
    1.3.16 Graphs
    1.3.17 Getting help
    1.3.18 Recoding of variables
    1.3.19 Linear regression
    1.4 Do-files
    1.5 Exiting Stata
    1.6 Exercises
  1. Working with do-files
    2.1 From interactive work to working with a do-file
    2.1.1 Alternative 1
    2.1.2 Alternative 2
    2.2 Designing do-files
    2.2.1 Comments
    2.2.2 Line breaks
    2.2.3 Some crucial commands
    2.3 Organizing your work
    2.4 Exercises Summary
  1. The grammar of Stata
    3.1 The elements of Stata commands
    3.1.1. Stata commands
    3.1.2 The variable list
    List of variables: required or optionals
    Abbreviation rules
    Special listings
    3.1.3 Options
    3.1.4 The in qualifier
    3.1.5 The if qualifier
    3.1.6 Expressions
    Operators
    Functions
    3.1.7 Lists of numbers
    3.1.8 Using filenames
    3.2 Repeating similar commands
    3.2.1 The by prefix
    3.2.2 The foreach loop
    The types of foreach lists
    Several commands within a foreach loop
    3.2.3 The forvalues loop
    3.3 Weights
    Frequency weights
    Analytic weights
    Probability weights
    3.4 Exercises
  1. General comments on the statistical commands
    4.1 Exercises
  1. Creating and changing variables
    5.1 The commands generate and replace
    5.1.1 Variable names
    5.1.2 Some examples
    5.1.3 Changing codes with by, _n, and _N
    5.1.4 Subscripts
    5.2 Specialized recoding commands
    5.2.1 The recode command
    5.2.2 The egen command
    5.3 More tools for recording data
    5.3.1 String functions
    5.3.2 Date and time functions
    Dates
    Times
    5.4 Commands for dealing with missing values
    5.5 Labels
    5.6 Storage types, or, the ghost in the machine
    5.7 Exercises
  1. Creating and changing graphs
    6.1 A primer on graph syntax
    6.2 Graph types
    6.2.1 Examples
    6.2.2 Specialized graphs
    6.3 Graph elements
    6.3.1 Appearance of data
    Choice of marker
    Marker colors
    Marker size
    Lines
    6.3.2 Graphs and plot regions
    Graph size
    Plot region
    Scaling the axes
    6.3.3 Information inside the plot region
    Reference lines
    Labeling inside the plot region
    6.3.4 Information outside the plot region
    Labeling the axes
    Tick lines
    Axis titles
    The legend
    Graph titles
    6.4 Multiple graphs
    6.4.1 Overlaying numerous twoway graphs
    6.4.2 Option by()
    6.4.3 Combining graphs
    6.5 Saving and printing graphs
    6.6 Exercises
  1. Describing and Comparing Distributions
    7.1 Categories: Few or many?
    7.2 Variables with few categories
    7.2.1 Tables
    Frequency tables
    More than one frequency table
    Comparing distributions
    Summary statistics
    More than one contingency table
    7.2.2 Graphs
    Histograms
    Bar charts
    Bar charts
    Dot chart
    7.3 Variables with many categories
    7.3.1 Frequencies of grouped data
    Some remarks on grouping data
    Special techniques for grouping data
    7.3.2 Describing data using statistics
    Important summary statistics
    The summarize command
    The tabstat command
    Comparing distributions using statistics
    7.3.3 Graphs
    Box plots
    Histograms
    Kernel density estimation
    Quantile plot
    Comparing distributions with Q–Q plots
    7.4 Exercises
  1. Introduction to Linear Regression
    8.1 Simple linear regression
    8.1.1 The basic principle
    8.1.2 Linear regression using Stata
    The table of coefficients
    Standard errors
    The table of ANOVA results
    The model fit table
    8.2 Multiple regression
    8.2.1 Multiple regression using Stata
    8.2.2 Additional components
    Adjusted R2
    Standardized regression coefficients
    8.2.3 What does "under control" mean?
    8.3 Regression diagnostics
    8.3.1 Violation of E(ei) = 0
    Linearity
    Influential cases
    Omitted variables
    8.3.2 Violation of Var(ei) = s2
    8.3.3 Violation of Cov(ei, ej) = 0, i ? j
    8.4 Model extensions
    8.4.1 Categorical independent variables
    8.4.2 Interaction terms
    8.4.3 Regression models using transformed variables
    Nonlinear relations
    Eliminating heteroskedasticity
    8.5 More on standard errors
    8.5.1 Bootstrap techniques
    8.5.2 Confidence intervals on cluster samples
    8.6 Advanced techniques
    8.6.1 Median regression
    8.6.2 Regression models for panel data
    From wide to long format
    Fixed-effects models
    8.6.3 Error-component models
    8.7 Exercises
  1. Regression models for Categorical Dependent Variables
    9.1 The linear probability model
    9.2 Basic concepts
    9.2.1 Odds, log odds, and odds ratios
    9.2.2 Excursion: The maximum likelihood principle
    9.3 Logistic regression with Stata
    9.3.1 The coefficients block
    Sign interpretation
    Interpretation with odds ratios
    Probability interpretation
    9.3.2 The iteration block
    9.3.3 The model fit block
    Classification tables
    Pearson chi-squared
    9.4 Logistic regression diagnostics
    9.4.1 Linearity
    9.4.2 Influential cases
    9.5 Likelihood-ratio test
    9.6 Refined models
    9.6.1 Nonlinear relationships
    9.6.2 Categorical independent variables
    9.6.3 Interaction effects
    9.7 Advanced techniques
    9.7.1 Probit models
    9.7.2 Multinomial logistic regression
    9.7.3 Models for ordinal data
    9.8 Exercises
  1. Reading and writing data
    10.1 The goal: The data matrix
    10.2 Importing machine-readable data
    10.2.1 Reading system files from other packages
    10.2.2 Reading ASCII text files
    Reading data in spreadsheet format
    Reading data in free format
    Reading data in fixed format
    10.3 Inputting data
    10.3.1 Input data using the editor
    10.3.2 The input command
    10.4 Combining data
    10.4.1 The GSOEP database
    10.4.2 The merge command
    The merge procedure
    Keeping track of observations
    Merging more than two files
    Merging data on different levels
    10.4.3 The append command
    10.5 Saving and exporting data
    10.6 Handling big datasets
    10.6.1 Rules for handling the working memory
    10.6.2 Using oversized datasets
    10.7 Exercises
  1. Do-files for advanced users and user-written programs
    11.1 Two examples of usage
    11.2 Four programming tools
    11.2.1 Local macros
    Calculating with local macros
    Combining local macros
    Changing local macros
    11.2.2 Do-files
    11.2.3 Programs
    The problem of redefinition
    The problem of naming
    The problem of error checking
    11.2.4 Programs in do-files and ado-files
    11.3 User-written Stata commands
    11.3.1 Parsing variable lists
    11.3.2 Parsing options
    11.3.3 Parsing if and in qualifiers
    11.3.4 Generating an unknown number of variables
    11.3.5 Default values
    11.3.6 Extended macro functions
    11.3.7 Avoiding changes in the dataset
    11.3.8 Help files
    11.4 Exercises
  1. Around Stata
    12.1 Resources and information
    12.2 Taking care of Stata
    12.3 Additional procedures
    12.3.1 SJ and STB ado-files
    12.3.2 SSC ado-files
    12.3.3 Other ado-files
    12.4 Exercises

References

Authors Index

Subject Index


  
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