Assiduously combining theory with plenty of practical, technical advice – and accompanied by original case studies and data sets – this book makes sure that students both understand Stata and know exactly what to do to make it meet their needs.

Research and statistics 1.1 The methodology of statistical research 1.2 The statistical method 1.3 The logic behind statistical inference 1.4 General laws and theories 1.5 Quantitative research papers 2. Introduction to Stata 2.1 What is Stata? 2.2 Entering and importing data into Stata 2.3 Data management 2.4 Descriptive statistics and graphs 2.5 Bivariate inferential statistics 3. Simple (bivariate) regression 3.1 What is regression analysis? 3.2 Simple linear regression analysis 3.3 Example in Stata 4. Multiple regression 4.1 Multiple linear regression analysis 4.2 Example in Stata 5. Dummy-Variable Regression 5.1 Why dummy-variable regression? 5.2 Regression with one dummy variable 5.3 Regression with one dummy variable and a covariate 5.4 Regression with more than one dummy variable 5.5 Regression with more than one dummy variable and a covariate 5.6 Regression with two separate sets of dummy variables 6. Interaction/moderation effects using regression 6.1 Interaction/moderation effect 6.2 Product-term approach 7. Linear regression assumptions and diagnostics 7.1 Correct specification of the model 7.2 Assumptions about residuals 7.3 Influential observations 8. Logistic regression 8.1 What is logistic regression? 8.2 Assumptions of logistic regression 8.3 Conditional effects 8.4 Diagnostics 8.5 Multinomial logistic regression 8.6 Ordered logistic regression 9. Multilevel analysis 9.1 Multilevel data 9.2 Empty or intercept-only model 9.3 Variance partition / intraclass correlation 9.4 Random intercept model 9.5 Level-2 explanatory variables 9.6 Logistic multilevel model 9.7 Random coefficient (slope) model 9.8 Interaction effects 9.9 Three-level models 10. Panel data analysis 10.1 Panel data 10.2 Pooled OLS 10.3 Between effects 10.4 Fixed effects (within estimator) 10.5 Random effects 10.6 Time-series cross-section methods 10.7 Binary dependent variables 11. Exploratory factor analysis 11.1 What is factor analysis? 11.2 Factor analysis process 11.3 Composite scores and reliability test 11.4 Example in Stata 12. Structural equation modelling and confirmatory factor analysis 12.1 What is structural equation modelling? 12.2 Confirmatory factor analysis 12.3 Latent path analysis 13. Critical issues 13.1 Transformation of variables 13.2 Weighting cases 13.3 Robust regression 13.4 Missing data