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

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

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

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

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

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

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

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?

Inferential Statistics Based on analysis of samples, we can make generalizations about the population of interest H 0 : Sleep deprivation does not impair performance H 1 : 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

Three Basic Statistical Methods 1)T-Test 2)Analysis of Variance (ANOVA) 3)Multiple Regression

Three Basic Statistical Methods 2)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

Three Basic Statistical Methods 2)Analysis of Variance (ANOVA)

Three Basic Statistical Methods 2)Analysis of Variance (ANOVA) Examples Psychology experiments Voter intentions Geographical differences

Three Basic Statistical Methods 3)Multiple Regression Continuous data But can also handle categorical data (subsumes ANOVA) Y = b 0 + b 1 X 1 + b 2 X b k X k

Three Basic Statistical Methods 3)Multiple Regression Y = b 0 + b 1 X 1 + b 2 X 2 + b 3 X 1 X 2

Three Basic Statistical Methods 3)Multiple Regression

Advanced Statistical Techniques Structural Equation Modeling

Advanced Statistical Techniques Structural Equation Modeling Extraversion FriendlyDaringTalkative Risky Sexual Behavior Casual Sex STI Testing Condom Use

Advanced Statistical Techniques Structural Equation Modeling Hierarchical Linear Modeling

Advanced Statistical Techniques Hierarchical Linear Modeling Tbilisi State University Ilya Chavchavdze University University of Western Ontario Teaching Method A Teaching Method B Teaching Method A Teaching Method B

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)

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.)

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

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)

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