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Research Methods for the Social Sciences Lorne Campbell Christopher J. Wilbur University of Western Ontario
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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
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Interactionist Perspective Behavior is a function of both context and individual differences – E.g., extraversion and social dominance
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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
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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
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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
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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
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Inferential Statistics
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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?
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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
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Three Basic Statistical Methods 1)T-Test 2)Analysis of Variance (ANOVA) 3)Multiple Regression
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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
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Three Basic Statistical Methods 2)Analysis of Variance (ANOVA)
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Three Basic Statistical Methods 2)Analysis of Variance (ANOVA) Examples Psychology experiments Voter intentions Geographical differences
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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 2 +... + b k X k
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Three Basic Statistical Methods 3)Multiple Regression Y = b 0 + b 1 X 1 + b 2 X 2 + b 3 X 1 X 2
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Three Basic Statistical Methods 3)Multiple Regression
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Advanced Statistical Techniques Structural Equation Modeling
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Advanced Statistical Techniques Structural Equation Modeling Extraversion FriendlyDaringTalkative Risky Sexual Behavior Casual Sex STI Testing Condom Use
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Advanced Statistical Techniques Structural Equation Modeling Hierarchical Linear Modeling
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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
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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)
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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.)
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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
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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)
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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
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