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Applied Statistics Using Stata: A Guide for the Social Sciences

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Authors:	Mehmet Mehmetoglu and Tor Georg Jakobsen
Publisher:	Sage
Copyright:	2017
ISBN-13:	978-1-4739-1323-3
Pages:	356; paperback

Authors:	Mehmet Mehmetoglu and Tor Georg Jakobsen
Publisher:	Sage
Copyright:	2017
ISBN-13:
Pages:	356; eBook
Price:	$0.00

Authors:	Mehmet Mehmetoglu and Tor Georg Jakobsen
Publisher:	Sage
Copyright:	2017
ISBN-13:
Pages:	356; Kindle
Price:	$

Comment from the Stata technical group

Applied Statistics Using Stata: A Guide for the Social Sciences, by Mehmet Mehmetoglu and Tor Georg Jakobsen, provides an introduction to using Stata for applied statistics. Graduate students from the social sciences, as well as anyone new to quantitative research using Stata, can benefit from this guide. Containing concepts from linear regression analysis to more advanced structural equation modeling, this book will give the reader a broad understanding of how to conduct statistical analysis using Stata.

The authors begin by providing a strong background on statistical concepts and a practical introduction to the applications of Stata. The authors explain critical concepts regarding statistical inference and regression analysis. They then guide the reader through the Stata interface, commands, and resources available for help.

After establishing the necessary statistical and software skill sets, the authors cover many statistical models. The authors transition smoothly from linear regression to logistic regression and factor analysis, while discussing the key assumptions related to each model. The authors illustrate each concept with an example using downloadable datasets, allowing readers to perform the sample statistical analyses as they read along. Each example is followed by a detailed interpretation of the statistical output and appropriate postestimation tests.

For readers who want to delve deeper into the topics covered, the authors provide a list of suggested reading in each chapter.

In short, this book's approach is designed to ensure a complete understanding of applied statistics using Stata.

View table of contents >>

Companion Website

About the Authors

Preface

1 RESEARCH AND STATISTICS

1.1 The methodology of statistical research
1.2 The statistical method
1.3 The logic behind statistical inference

1.3.1 Probability theory
1.3.2 Population size
1.3.3 Why do I need significance levels if I am investigating the whole population?

1.4 General laws and theories

1.4.1 Objectivity and critical realism

1.5 Quantitative research papers
1.6 Concluding remarks
Questions
Further reading
References

2 INTRODUCTION TO STATA

2.1 What is Stata?

2.1.1 The Stata interface
2.1.2 How to use Stata

2.2 Entering and importing data into Stata

2.2.1 Entering data
2.2.2 Importing data

2.3 Data management

2.3.1 Opening data
2.3.2 Examining data
2.3.3 Making changes to variables
2.3.4 Generating variables
2.3.5 Subsetting data
2.3.6 Labelling variables

2.4 Descriptive statistics and graphs

2.4.1 Frequency distributions
2.4.2 Summary statistics
2.4.3 Appending data
2.4.4 Merging data
2.4.5 Reshaping data

2.5 Bivariate inferential statistics

2.5.1 Correlation
2.5.2 Independent t-test
2.5.3 Analysis of variance (ANOVA)
2.5.4 Chi-squared test

2.6 Conclusion
Questions
Further reading

3 SIMPLE (BIVARIATE) REGRESSION

3.1 What is regression analysis?
3.2 Simple linear regression analysis

3.2.1 Ordinary least squares
3.2.2 Goodness of fit
3.2.3 Hypothesis test for slope coefficient
3.2.4 Prediction in linear regression

3.3 Example in Stata
3.4 Conclusion
Questions
Further reading
References

4 MULTIPLE REGRESSION

4.1 Multiple linear regression analysis

4.1.1 Estimation
4.1.2 Goodness of fit and the F-test
4.1.3 Adjusted R²
4.1.4 Partial slope coefficients
4.1.5 Prediction in multiple regression
4.1.6 Standardization and relative importance

4.2 Example in Stata
4.3 Conclusion
Questions
Further reading
References

5 DUMMY-VARIABLE REGRESSION

5.1 Why dummy-variable regression?

5.1.1 Creating dummy variables
5.1.2 The logic behind dummy-variable regression

5.2 Regression with one dummy variable

5.2.1 Example in Stata

5.3 Regression with one dummy variable and a covariate

5.3.1 Example in Stata

5.4 Regression with more than one dummy variable

5.4.1 Example in Stata
5.4.2 Comparing the included groups

5.5 Regression with more than one dummy variable and a covariate

5.5.1 Example in Stata

5.6 Regression with two separate sets of dummy variables

5.6.1 Example in Stata

5.7 Conclusion
Questions
Further reading
References

6 INTERACTION/MODERATION EFFECTS USING REGRESSION

6.1 Interaction/moderation effect
6.2 Product-term approach

6.2.1 Interaction between a continuous predictor and a continuous moderator
6.2.2 Interaction between a continuous predictor and a dummy moderator
6.2.3 Interaction between a dummy predictor and a dummy moderator
6.2.4 Interaction between a continuous predictor and a polytomous moderator

6.3 Conclusion
Questions
Further reading
References

7 LINEAR REGRESSION ASSUMPTIONS AND DIAGNOSTICS

7.1 Correct specification of the model

7.1.1 All X-variables relevant, and none irrelevant
7.1.2 Linearity
7.1.3 Additivity
7.1.4 Absence of multicollinearity

7.2 Assumptions about residuals

7.2.1 That the error term has a conditional mean of zero
7.2.2 Homoskedasticity
7.2.3 Uncorrelated errors
7.2.4 Normally distributed errors

7.3 Influential observations

7.3.1 Leverage
7.3.2 DFBETA
7.3.3 Cook's distance

7.4 Conclusion
Questions
Further reading
References

8 LOGISTIC REGRESSION

8.1 What is logistic regression?

8.1.1 Tests of significance

8.2 Assumptions of logistic regression

8.2.1 Example in Stata

8.3 Conditional effects
8.4 Diagnostics
8.5 Multinomial logistic regression
8.6 Ordered logistic regression
8.7 Conclusion
Questions
Further reading
References

9 MULTILEVEL ANALYSIS

9.1 Multilevel data

9.1.1 Statistical reasons for using multilevel analysis

9.2 Empty or intercept-only model

9.2.1 Example in Stata

9.3 Variance partition or intraclass correlation
9.4 Random-intercept model
9.5 Level-2 explanatory variables

9.5.1 How much of the dependent variable is explained?

9.6 Logistic multilevel model
9.7 Random-coefficient (slope) model
9.8 Interaction effects
9.9 Three-level models

9.9.1 Cross-classified multilevel model

9.10 Weighting
9.11 Conclusion
Questions
Further reading
References

10 PANEL DATA ANALYSIS

10.1 Panel data
10.2 Pooled OLS
10.3 Between effects
10.4 Fixed effects (within estimator)

10.4.1 Explaining fixed effects
10.4.2 Summary of fixed effects
10.4.3 Time-fixed effects

10.5 Random effects
10.6 Time-series cross-section methods

10.6.1 Testing for non-stationarity
10.6.2 Lag selection
10.6.3 The TSCS model

10.7 Binary dependent variables
10.8 Conclusion
Questions
Further reading
References

11 EXPLORATORY FACTOR ANALYSIS

11.1 What is factor analysis?

11.1.1 What is factor analysis used for?

11.2 The factor analysis process

11.2.1 Extracting the factors
11.2.2 Determining the number of factors
11.2.3 Rotating the factors
11.2.4 Refining and interpreting the factors

11.3 Composite scores and reliability test
11.4 Example in Stata
11.5 Conclusion
Questions
Further reading
References

12 STRUCTURAL EQUATION MODELLING AND CONFIRMATORY FACTOR ANALYSIS

12.1 What is structural equation modelling?

12.1.1 Types of structural equation modelling

12.2 Confirmatory factor analysis

12.2.1 Model specification
12.2.2 Model identification
12.2.3 Parameter estimation
12.2.4 Model assessment
12.2.5 Model modification

12.3 Latent path analysis

12.3.1 Specification of the LPA model
12.3.2 Measurement part
12.3.3 Structural part

12.4 Conclusion
Questions
Further reading
References

13 CRITICAL ISSUES

13.1 Transformation of variables

13.1.1 Skewness and kurtosis
13.1.2 Transformations

13.2 Weighting cases
13.3 Robust regression
13.4 Missing data

13.4.1 Traditional methods for handling missing data
13.4.2 Multiple imputation

13.5 Conclusion
Questions
Further reading
References

Index

Stata: Data Analysis and Statistical Software

Applied Statistics Using Stata: A Guide for the Social Sciences

Comment from the Stata technical group

Table of contents

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Stata/MP4 Annual License (download)

Stata: Data Analysis and Statistical Software

Applied Statistics Using Stata: A Guide for the Social Sciences

VitalSource eBook details

How to access your eBook

Return policy for eBooks

Comment from the Stata technical group

Table of contents

Stata

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