Data Analysis Using Stata-经管之家官网！

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做完这本书 本人制作电子版的工作就得告一段落了 因为我就只有这几本书了

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补缺页63

Table of contents
Preface (pdf)
0 About the book

0.1 Structure
0.2 Using this book: Materials and hints
0.3 Teaching with this manual
1 "The first time"

1.1 Starting Stata
1.2 Setting up your screen
1.3 Your first analysis
1.4 Do-files
1.5 Exiting Stata
2 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 Summary
3 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 optional

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
3.2.3 The forvalues loop
3.3 Weights
4 Some general comments on the statistical commands
5 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 Additional tools for recording data
5.3.1 String functions
5.3.2 Date functions
5.4 Commands for dealing with missing values
5.5 Labels
5.6 Storage types, or, the ghost in the machine
6 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 Graph 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
7 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

7.2.2 Graphs
Histograms

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

7.3.4 Summary
7.4 Summary
8 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 computations
8.2.3 What does "under control" mean?
8.3 Regression diagnostics
8.3.1 Violation of E(εi) = 0
Linearity

Influential cases

Omitted variables

8.3.2 Violation of Var(εi) = σ2
8.3.3 Violation of Cov(εi, εj) = 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 in 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 Summary
9 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
9.7 Advanced techniques
9.7.1 Probit models
9.7.2 Multinomial logistic regression
9.7.3 Models for ordinal data
9.8 Summary
10 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 Summary
11 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
11.2.2 Do-files
11.2.3 Programs
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 Summary
12 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 Summary
References

Author index (pdf)

Subject index (pdf)

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