目录

```1 Getting started
1.1 Conventions
1.2 Introduction
1.3 The Stata screen
1.4 Using an existing dataset
1.5 An example of a short Stata session
1.6 Summary
1.7 Exercises

2 Entering data
2.1 Creating a dataset
2.2 An example questionnaire
2.3 Develop a coding system
2.4 Entering data using the Data Editor

2.4.1 Value labels

2.5 The Variables Manager
2.6 The Data Editor (Browse) view
2.8 Checking the data
2.9 Summary
2.10 Exercises

3 Preparing data for analysis
3.1 Introduction
3.3 Creating value labels
3.4 Reverse-code variables
3.5 Creating and modifying variables
3.6 Creating scales
3.7 Save some of your data
3.8 Summary
3.9 Exercises

4 Working with commands, do-files, and results
4.1 Introduction
4.2 How Stata commands are constructed
4.3 Creating a do-file
4.4 Copying your results to a word processor
4.6 Summary
4.7 Exercises

5 Descriptive statistics and graphs for one variable
5.1 Descriptive statistics and graphs
5.2 Where is the center of a distribution?
5.3 How dispersed is the distribution?
5.4 Statistics and graphs—unordered categories
5.5 Statistics and graphs—ordered categories and variables
5.6 Statistics and graphs—quantitative variables
5.7 Summary
5.8 Exercises

6 Statistics and graphs for two categorical variables
6.1 Relationship between categorical variables
6.2 Cross-tabulation
6.3 Chi-squared test

6.3.1 Degrees of freedom
6.3.2 Probability tables

6.4 Percentages and measures of association
6.5 Odds ratios when dependent variable has two categories
6.6 Ordered categorical variables
6.7 Interactive tables
6.8 Tables—linking categorical and quantitative variables
6.9 Power analysis when using a chi-squared test of significance
6.10 Summary
6.11 Exercises

7 Tests for one or two means
7.1 Introduction to tests for one or two means
7.2 Randomization
7.3 Random sampling
7.4 Hypotheses
7.5 One-sample test of a proportion
7.6 Two-sample test of a proportion
7.7 One-sample test of means
7.8 Two-sample test of group means

7.8.1 Testing for unequal variances

7.9 Repeated-measures t test
7.10 Power analysis
7.11 Nonparametric alternatives

7.11.1 Mann–Whitney two-sample rank-sum test
7.11.2 Nonparametric alternative: Median test

7.12 Summary
7.13 Exercises

8 Bivariate correlation and regression
8.1 Introduction to bivariate correlation and regression
8.2 Scattergrams
8.3 Plotting the regression line
8.4 Correlation
8.5 Regression
8.6 Spearman’s rho: Rank-order correlation for ordinal data
8.7 Summary
8.8 Exercises

9 Analysis of variance
9.1 The logic of one-way analysis of variance
9.2 ANOVA example
9.3 ANOVA example using survey data
9.4 A nonparametric alternative to ANOVA
9.5 Analysis of covariance
9.6 Two-way ANOVA
9.7 Repeated-measures design
9.8 Intraclass correlation—measuring agreement
9.9 Summary
9.10 Exercises

10 Multiple regression
10.1 Introduction to multiple regression
10.2 What is multiple regression?
10.3 The basic multiple regression command
10.4 Increment in R-squared: Semipartial correlations
10.5 Is the dependent variable normally distributed?
10.6 Are the residuals normally distributed?
10.7 Regression diagnostic statistics

10.7.1 Outliers and influential cases
10.7.2 Influential observations: DFbeta
10.7.3 Combinations of variables may cause problems

10.8 Weighted data
10.9 Categorical predictors and hierarchical regression
10.10 A shortcut for working with a categorical variable
10.11 Fundamentals of interaction
10.12 Power analysis in multiple regression
10.13 Summary
10.14 Exercises

11 Logistic regression
11.1 Introduction to logistic regression
11.2 An example
11.3 What is an odds ratio and a logit?

11.3.1 The odds ratio
11.3.2 The logit transformation

11.4 Data used in rest of chapter
11.5 Logistic regression
11.6 Hypothesis testing

11.6.1 Testing individual coefficients
11.6.2 Testing sets of coefficients

11.7 Nested logistic regressions
11.8 Power analysis when doing logistic regression
11.9 Summary
11.10 Exercises

12 Measurement, reliability, and validity
12.1 Overview of reliability and validity
12.2 Constructing a scale

12.2.1 Generating a mean score for each person

12.3 Reliability

12.3.1 Stability and test–retest reliability
12.3.2 Equivalence
12.3.3 Split-half and alpha reliability—internal consistency
12.3.4 Kuder–Richardson reliability for dichotomous items
12.3.5 Rater agreement—kappa (K)
12.4 Validity

12.4.1 Expert judgment
12.4.2 Criterion-related validity
12.4.3 Construct validity

12.5 Factor analysis
12.6 PCF analysis

12.6.1 Orthogonal rotation: Varimax
12.6.2 Oblique rotation: Promax

12.7 But we wanted one scale, not four scales

12.7.1 Scoring our variable

12.8 Summary
12.9 Exercises

13 Working with missing values—multiple imputation
13.1 The nature of the problem
13.2 Multiple imputation and its assumptions about the mechanism for missingness
13.3 What variables do we include when doing imputations?
13.4 Multiple imputation
13.5 A detailed example

13.5.1 Preliminary analysis
13.5.2 Setup and multiple-imputation stage
13.5.3 The analysis stage
13.5.4 For those who want an R2 and standardized βs
13.5.5 When impossible values are imputed

13.6 Summary
13.7 Exercises

A What’s next?
A.1 Introduction to the appendix
A.2 Resources

A.2.1 Web resources