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书籍名称:Data Analysis Using Stata, Third Edition
出版社:Stata Press
作者: Ulrich Kohler and Frauke Kreuter
出版时间:2012
语种: 英文
页数: 497
印刷日期:2012
开本: 胶版纸
纸张:497 I S B N: 978-1-59718-110-5
装订: 平装

简介

Data Analysis Using Stata, Third Edition has been completely revamped to reflect the capabilities of Stata 12. This book will appeal to those just learning statistics and Stata, as well as to the many users who are switching to Stata from other packages. Throughout the book, Kohler and Kreuter show examples using data from the German Socio-Economic Panel, a large survey of households containing demographic, income, employment, and other key information. Kohler and Kreuter take a hands-on approach, first showing how to use Stata’s graphical interface and then describing Stata’s syntax. The core of the book covers all aspects of social science research, including data manipulation, production of tables and graphs, linear regression analysis, and logistic modeling. The authors describe Stata’s handling of categorical covariates and show how the new margins and marginsplot commands greatly simplify the interpretation of regression and logistic results. An entirely new chapter discusses aspects of statistical inference, including random samples, complex survey samples, nonresponse, and causal inference. The rest of the book includes chapters on reading text files into Stata, writing programs and do-files, and using Internet resources such as the search command and the SSC archive. Data Analysis Using Stata, Third Edition has been structured so that it can be used as a self-study course or as a textbook in an introductory data analysis or statistics course. It will appeal to students and academic researchers in all the social sciences.

目录

    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 Defining missing values 
    1.3.12 The by prefix 
    1.3.13 Command options 
    1.3.14 Frequency tables 
    1.3.15 Graphs 
    1.3.16 Getting help 
    1.3.17 Recoding variables 
    1.3.18 Variable labels and value labels 
    1.3.19 Linear regression 
    
    1.4 Do-files 
    1.5 Exiting Stata 
    1.6 Exercises 
    
    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 Exercises 
    
    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 
    
    The types of foreach lists 
    Several commands within a foreach loop 
    
    3.2.3 The forvalues loop 
    
    3.3 Weights 
    
    Frequency weights 
    Analytic weights 
    Sampling weights 
    
    3.4 Exercises 
    
    4 General comments on the statistical commands 
    4.1 Regular statistical commands 
    4.2 Estimation commands 
    4.3 Exercises 
    
    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 Useful functions 
    5.1.4 Changing codes with by, n, and N 
    5.1.5 Subscripts 
    
    5.2 Specialized recoding commands 
    
    5.2.1 The recode command 
    5.2.2 The egen command 
    
    5.3 Recoding string variables 
    5.4 Recoding date and time 
    
    5.4.1 Dates 
    5.4.2 Time 
    
    5.5 Setting missing values 
    5.6 Labels 
    5.7 Storage types, or the ghost in the machine 
    5.8 Exercises 
    
    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 many twoway graphs 
    6.4.2 Option by() 
    6.4.3 Combining graphs 
    
    6.5 Saving and printing graphs 
    6.6 Exercises 
    
    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 
    More than one contingency table 
    
    7.2.2 Graphs 
    
    Histograms 
    Bar charts 
    Pie charts 
    Dot charts 
    
    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 
    
    8 Statistical inference 
    8.1 Random samples and sampling distributions 
    
    8.1.1 Random numbers 
    8.1.2 Creating fictitious datasets 
    8.1.3 Drawing random samples 
    8.1.4 The sampling distribution 
    
    8.2 Descriptive inference 
    
    8.2.1 Standard errors for simple random samples 
    8.2.2 Standard errors for complex samples 
    
    Typical forms of complex samples 
    Sampling distributions for complex samples 
    Using Stata’s svy commands 
    
    8.2.3 Standard errors with nonresponse 
    
    Unit nonresponse and poststratification weights 
    Item nonresponse and multiple imputation 
    
    8.2.4 Uses of standard errors 
    
    Confidence intervals 
    Significance tests 
    Two-group mean comparison test 
    
    8.3 Causal inference 
    
    8.3.1 Basic concepts 
    
    Data-generating processes 
    Counterfactual concept of causality 
    
    8.3.2 The effect of third-class tickets 
    8.3.3 Some problems of causal inference 
    
    8.4 Exercises 
    
    9 Introduction to linear regression 
    9.1 Simple linear regression 
    
    9.1.1 The basic principle 
    9.1.2 Linear regression using Stata 
    
    The table of coefficients 
    The table of ANOVA results 
    The model fit table 
    
    9.2 Multiple regression 
    
    9.2.1 Multiple regression using Stata 
    9.2.2 More computations 
    
    Adjusted R2 
    Standardized regression coefficients 
    
    9.2.3 What does “under control” mean? 
    
    9.3 Regression diagnostics 
    
    9.3.1 Violation of E(εi) = 0 
    
    Linearity 
    Influential cases 
    Omitted variables 
    Multicollinearity 
    
    9.3.2 Violation of Var(εi) = σ2 
    9.3.3 Violation of Cov(εi, εj) = 0, i ≠ j 
    
    9.4 Model extensions 
    
    9.4.1 Categorical independent variables 
    9.4.2 Interaction terms 
    9.4.3 Regression models using transformed variables 
    
    Nonlinear relationships 
    Eliminating heteroskedasticity 
    
    9.5 Reporting regression results 
    
    9.5.1 Tables of similar regression models 
    9.5.2 Plots of coefficients 
    9.5.3 Conditional-effects plots 
    
    9.6 Advanced techniques 
    
    9.6.1 Median regression 
    9.6.2 Regression models for panel data 
    
    From wide to long format 
    Fixed-effects models 
    
    9.6.3 Error-components models 
    
    9.7 Exercises 
    
    10 Regression models for categorical dependent variables 
    10.1 The linear probability model 
    10.2 Basic concepts 
    
    10.2.1 Odds, log odds, and odds ratios 
    10.2.2 Excursion: The maximum likelihood principle 
    
    10.3 Logistic regression with Stata 
    
    10.3.1 The coefficient table 
    
    Sign interpretation 
    Interpretation with odds ratios 
    Probability interpretation 
    Average marginal effects 
    
    10.3.2 The iteration block 
    10.3.3 The model fit block 
    
    Classification tables 
    Pearson chi-squared 
    
    10.4 Logistic regression diagnostics 
    
    10.4.1 Linearity 
    10.4.2 Influential cases 
    
    10.5 Likelihood-ratio test 
    10.6 Refined models 
    
    10.6.1 Nonlinear relationships 
    10.6.2 Interaction effects 
    
    10.7 Advanced techniques 
    
    10.7.1 Probit models 
    10.7.2 Multinomial logistic regression 
    10.7.3 Models for ordinal data 
    
    10.8 Exercises 
    
    11 Reading and writing data 
    11.1 The goal: The data matrix 
    11.2 Importing machine-readable data 
    
    11.2.1 Reading system files from other packages 
    
    Reading Excel files 
    Reading SAS transport files 
    Reading other system files 
    
    11.2.2 Reading ASCII text files 
    
    Reading data in spreadsheet format 
    Reading data in free format 
    Reading data in fixed format 
    
    11.3 Inputting data 
    
    11.3.1 Input data using the Data Editor 
    11.3.2 The input command 
    
    11.4 Combining data 
    
    11.4.1 The GSOEP database 
    11.4.2 The merge command 
    
    Merge 1:1 matches with rectangular data 
    Merge 1:1 matches with nonrectangular data 
    Merging more than two files 
    Merging m:1 and 1:m matches 
    
    11.4.3 The append command 
    
    11.5 Saving and exporting data 
    11.6 Handling large datasets 
    
    11.6.1 Rules for handling the working memory 
    11.6.2 Using oversized datasets 
    
    11.7 Exercises 
    
    12 Do-files for advanced users and user-written programs 
    12.1 Two examples of usage 
    12.2 Four programming tools 
    
    12.2.1 Local macros 
    
    Calculating with local macros 
    Combining local macros 
    Changing local macros 
    
    12.2.2 Do-files 
    12.2.3 Programs 
    
    The problem of redefinition 
    The problem of naming 
    The problem of error checking 
    
    12.2.4 Programs in do-files and ado-files 
    
    12.3 User-written Stata commands 
    
    12.3.1 Sketch of the syntax 
    12.3.2 Create a first ado-file 
    12.3.3 Parsing variable lists 
    12.3.4 Parsing options 
    12.3.5 Parsing if and in qualifiers 
    12.3.6 Generating an unknown number of variables 
    12.3.7 Default values 
    12.3.8 Extended macro functions 
    12.3.9 Avoiding changes in the dataset 
    12.3.10 Help files 
    
    12.4 Exercises 
    
    13 Around Stata 
    13.1 Resources and information 
    13.2 Taking care of Stata 
    13.3 Additional procedures 
    
    13.3.1 Stata Journal ado-files 
    13.3.2 SSC ado-files 
    13.3.3 Other ado-files 
    
    13.4 Exercises 
    
    References 
    Author index 
    Subject index