Research Methods for the Social Sciences

1. Research Methods for the Social Sciences Lorne Campbell Christopher J. Wilbur University of Western Ontario

2. Philosophy of Human Behavior • (1) Behavior is influenced by outside circumstances • Experimental approach • (2) Behavior is influenced by the qualities possessed by the individual • Correlational approach

3. Interactionist Perspective • Behavior is a function of both context and individual differences • E.g., extraversion and social dominance

4. Types of Research Methods • Runkel and McGrath • Developed a circumplex model to describe the goals of the research process, and the basic types of research methods available • Helps structure our thinking of the types of methods available, and the pros/cons of each type of method

5. B Obtrusive Research Operations Laboratory Experiments Experimental Simulations Judgment Tasks II II Field Experiments III I III I Sample Surveys Field Studies IV IV Unobtrusive Research Operations C Formal Theory Computer Simulations A Universal Behavioral Systems Particular Behavioral Systems

6. Benefits of Multi-Method Research • Mono-operation bias • When using the same method time after time, your research suffers from the same set of limitations • Using different methods to address the same question(s) helps overcome the limitation of each method • E.g., research on self-concept

7. Inferential Statistics • Inferential statistics are usually preferred to simply looking at differences because we can conclude with more certainty that the difference accurately characterizes the population

8. Inferential Statistics

9. Inferential Statistics • Inferential statistics are usually preferred to simply looking at differences because we can conclude with more certainty that the difference accurately characterizes the population • Is this difference a true difference in the general population or just a random effect based on the particular sample?

10. Inferential Statistics • Based on analysis of samples, we can make generalizations about the population of interest • H0: Sleep deprivation does not impair performance • H1: Sleep deprivation does impair performance • Compare two groups on performance measure • If a mean difference emerges that is unlikely by chance alone, we assume this difference is accurate of the population

11. Three Basic Statistical Methods • T-Test • Analysis of Variance (ANOVA) • Multiple Regression

12. Three Basic Statistical Methods • Analysis of Variance (ANOVA) • Categorical data (i.e., experimental conditions, demographic data) • Between-subjects or within-subjects • Can compare 3 or more conditions or groups • Can examine interactive effects of multiple variables

13. Three Basic Statistical Methods • Analysis of Variance (ANOVA)

14. Three Basic Statistical Methods • Analysis of Variance (ANOVA) • Examples • Psychology experiments • Voter intentions • Geographical differences

15. Three Basic Statistical Methods • Multiple Regression • Continuous data • But can also handle categorical data (subsumes ANOVA) • Y = b0 + b1X1 + b2X2 + ... + bkXk

16. Three Basic Statistical Methods • Multiple Regression • Y = b0 + b1X1 + b2X2 + b3X1X2

17. Three Basic Statistical Methods • Multiple Regression

18. Advanced Statistical Techniques • Structural Equation Modeling

19. Advanced Statistical Techniques • Structural Equation Modeling Extraversion Risky Sexual Behavior Talkative Condom Use Daring STI Testing Friendly Casual Sex

20. Advanced Statistical Techniques • Structural Equation Modeling • Hierarchical Linear Modeling

21. Advanced Statistical Techniques • Hierarchical Linear Modeling

22. Teaching Statistics • Bachelor’s Level • Year 2 • Introductory statistics course (mathematical; probabilities, logic of inferential statistics, t-tests, ANOVA, correlation/regression, some other assorted tests) • Year 3 • Advanced statistics course (logical; logic of the tests; application of the tests with SPSS)

23. Teaching Statistics • Masters Level • Year 1 • Advanced statistics course (refreshing and extending; large focus on t-tests, ANOVA, and correlation/multiple regression) • Beyond • Specialized courses in advanced topics (e.g., factor analysis, SEM, HLM, etc.)

24. How I have taught undergraduate courses on research methods • Brief version of syllabus • Week 1 – introduction to course • Week 2 – Validity and Reliability • Validity • Construct • Internal • External • Reliability • Psychometric properties of scales • Week 3 – Experimental design and the significance testing debate

25. Week 4 – Quasi-experimental designs • E.g., regression discontinuity design, field experiment • Week 5 – Field Studies, simulation methods • E.g., research by Doug Kenrick • Week 6 – Diary research • Week 7 – Multilevel modelling • Week 8 – Dyadic data (collection and analysis)

26. Week 9 – Social Relations Model (SRM) • E.g, loneliness study • Week 10 – Mediation and Moderation • Week 11 – Methods in Social Cognition • E.g., AMP model • Week 12 – Meta-analysis • Week 13 – Research Ethics