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Research Methods Outline

Research Methods Outline. Meta-analysis Correlation Quasi-Experiments Discuss Questionnaire Data Observational Research Activity: Observational Research. Meta-analysis.

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Research Methods Outline

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  1. Research MethodsOutline • Meta-analysis • Correlation • Quasi-Experiments • Discuss Questionnaire Data • Observational Research • Activity: Observational Research

  2. Meta-analysis • A set of statistical procedures for combining the results of a number of studies in order to provide a general assessment of the relationship between the variables • Tells us if there is a difference between groups • Tells us how strong the finding is, the effect size

  3. Example: Participation rate & leader emergence (Mullen, Salas, & Driskell, 1989) One of the strongest determinants of who emerges leader in a group is the member with the highest participation Example: Social loafing (Karau & Williams, 1989) Social loafing is greater for males than females and more pronounced as the size of the group increases Meta-Analysis Examples SOCIAL

  4. Researchers gather a set of observations about a group of people and test for associations between different variables Tells you whether 2 variables are associated with each other systematically Cannot prove cause-effect X could cause Y Y could cause X Z could cause X and Y (third variable problem) Correlational Research Method

  5. Measures the degree and direction of linear relationship between 2 variables Two parts to a correlation Strength Direction Positive or negative The Pearson Correlation Coefficient (r) Closer to 1 or –1 means stronger relationship Positive value indicates positive relationship, negative value is negative relationship Correlation

  6. Positive Correlations • As one variable goes up the other one goes up as well (or as one goes down the other goes down) • STRONG (r = 1.0) WEAKER ( r= .60)

  7. Negative Correlations • As one variable goes up the other one goes DOWN (or as one goes down the other goes up) • STRONG (r = -1.0) WEAKER ( r= -.60)

  8. Quasi-Experiments • Sometimes known as queasy-experiments • Can give experimental purists a queasy feeling • Researcher has only partial control over her/his independent variables • Participants assigned to 1 or more conditions by means other than random assignment • A correlational method in which real-world groups are compared on a DV.

  9. Out-group homogeneity effect Perceive out-group as more homogeneous (less diverse) than the in-group In-group bias Tendency to more favorably evaluate members of In-group EXAMPLE: Park and Rothbart (1982) 3 sororities Rate own and other 2 Results: Clear evidence of out-group homogeneity effect Clear evidence of in-group bias Quasi-ExperimentResearch Example

  10. Stereotype Threat (Steele) Stereotyped group is aware of the stereotype Creates apprehension and impaired performance EXAMPLE: Steele & Aronson, 1994 Difficult verbal test: Black & White Stanford students Two conditions: Testing intellectual ability Testing the test Results: When testing the test: B & W performed equally well When testing IQ= B poorer than W Yet another example…

  11. Class Questionnaire Data • Develop Hypotheses with these variables: • Comfort with working in groups and cooperation in last student project • Years playing team sports and preference to work in a group • Gender and teamwork attitude • Gender and leadership in student project • Gender and number of years in team sports

  12. Correlation Group Comfort and cooperation in group tasks r= -.27 Years and preference for groups r = + .33 Quasi-experiment Gender & teamwork attitude No difference Women and men: 5.15 Gender & leadership in student project Men report more leadership experience Men: 5.85, Women: 4.88 Gender & number of year of team experience Men report more years of team experience Women: 10.15, men:12.77 Class Questionnaire Data

  13. Final Questionnaire Issues • Social desirability bias • A bias resulting from participants giving responses that make them look good rather than giving honest responses • You completed 2 different scales: • LIKERT scale: Items typically asking whether participants strongly agree, agree, disagree, strongly disagree • SEMANTIC DIFFERENTIAL scale: Participants rate a given concept on a series of 7-point bipolar attitude scales • Summarizing open-ended question responses

  14. Observational Research • Observational methods • Nonexperimental methods in which observers watch groups to gather information • Methods vary with respect to • Degree to which observer is part of a group • Degree to which observations are structured

  15. Observational Research • Gender, group size, and amount of beer consumed (Geller, Russ, & Altomari) • Observed 56 females 187 males at local bars (students 18-25 years) • Results • Drank more in a group • Males drank more than females • Function of container type

  16. Unstructured Observational Methods • Unstructured: • Observers offer impressionistic, descriptive accounts of the group • Participant observation • Researcher becomes a member of the group being studied

  17. Unstructured Observational Methods • Participant observation examples: • Whyte (1943) • Joined Italian American gang in Boston • Festinger, Reiken, & Schachter (1956) • Joined ‘doomsday’ cult, pretended to believe in world ending • Ezekiel (1995) • Attended neo-Nazi and KKK groups to get an insider’s look • Martel (2001) • Joined Jewish Harley Davidson riders • Bock (2000) • Was member of ‘single moms by choice’ support group

  18. Criticisms of Participant Observation • By joining the group, they change it in some way • Groups are unaware they are being observed • May be unethical • People don’t liked to be spied on, feel betrayed, foolish • Observer bias • Hard to quantify unstructured data

  19. Structured Observational Methods • Structured • Quantitative methods in which group behaviors are observed and recorded with objective system • Researcher must meticulously develop coding system • Code things relevant to research • Coding system is lens of research • Interrater reliability • Extent to which the ratings of different observers are in agreement

  20. Interaction Process Analysis • Observational coding system developed by Bales to measure 6 task and 6 socioemotional activities in a group

  21. Interaction Process Analysis • Example (Hutson-Comeaux & Kelly, 1996) • Investigated whether female and male groups of college students differed in their interaction style • Found that females engaged in more positive socioemotional behavior and males engaged in more task-oriented behavior

  22. Class Activity: Studying Groups • Communication and content analysis • Castle building exercise

  23. Observational Research Discussion • Use your data to draw conclusions about the groups structure and process • Use the information from the communication analysis to identify the group’s leader as well as other members who were more or less active in the activity. • Use the information from the content analysis to identify the overall content of the groups discussion. (Items 1-3 and 10-12 are socioemotional activities, 4-9 are task activites, see Forsyth, p.32) • Report your findings to the class

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