Transcript Slide 1

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
B
Obtrusive
Research
Operations
Laboratory
Experiments
II
Judgment
Tasks
Experimental
Simulations
II
Field
Experiments
III
Sample
Surveys
I
III
I
IV
Unobtrusive
Research
Operations
Field
Studies
IV
C
Formal
Theory
Computer
Simulations
A
Universal
Behavioral Systems
Particular
Behavioral Systems
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
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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
Inferential Statistics
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
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Is this difference a true difference in the general
population or just a random effect based on the
particular sample?
Inferential Statistics
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Based on analysis of samples, we can make
generalizations about the population of interest
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H0: Sleep deprivation does not impair performance
H1: Sleep deprivation does impair performance
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Compare two groups on performance measure
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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)
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Categorical data (i.e., experimental conditions, demographic
data)
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Between-subjects or within-subjects
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Can compare 3 or more conditions or groups
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Can examine interactive effects of multiple variables
Three Basic Statistical Methods
2) Analysis of Variance (ANOVA)
7
6
Outcome Score
5
4
Control
3
Experimental
2
1
0
Men
Women
Three Basic Statistical Methods
2) Analysis of Variance (ANOVA)
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Examples
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Psychology experiments
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Voter intentions
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Geographical differences
Three Basic Statistical Methods
3) Multiple Regression
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Continuous data
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But can also handle categorical data (subsumes ANOVA)
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Y = b0 + b1X1 + b2X2 + ... + bkXk
Three Basic Statistical Methods
3) Multiple Regression
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Y = b0 + b1X1 + b2X2 + b3X1X2
Three Basic Statistical Methods
3) Multiple Regression
Advanced Statistical Techniques
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Structural Equation Modeling
Advanced Statistical Techniques
• Structural Equation Modeling
Risky
Sexual
Behavior
Extraversion
Talkative
Daring
Friendly
Condom
Use
STI
Testing
Casual
Sex
Advanced Statistical Techniques
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Structural Equation Modeling
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Hierarchical Linear Modeling
Advanced Statistical Techniques
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Hierarchical Linear Modeling
Tbilisi State
University
Ilya Chavchavdze
University
University of
Western Ontario
Teaching Method A
Teaching Method A
Teaching Method A
Teaching Method B
Teaching Method B
Teaching Method B
Teaching Method A
Teaching Method A
Teaching Method A
Teaching Method B
Teaching Method B
Teaching Method B
Teaching Statistics
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Bachelor’s Level
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Year 2
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Introductory statistics course (mathematical; probabilities, logic of
inferential statistics, t-tests, ANOVA, correlation/regression, some
other assorted tests)
Year 3
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Advanced statistics course (logical; logic of the tests; application of the
tests with SPSS)
Teaching Statistics
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Masters Level
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Year 1
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Advanced statistics course (refreshing and extending; large focus on ttests, ANOVA, and correlation/multiple regression)
Beyond
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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