Chapter 8 class version 2

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Chapter 8 class version 2

  1. 1. Chapter 8 -- Continued 10/16/2012
  2. 2. Roadmap Discuss:  Exam 2  Reflection Assignment #1 Quick Review of Weak and Strong Between- Participants designs New: Within-Participants and factorial designs
  3. 3. Experimental Research Design• Weak vs. Strong experimental design
  4. 4. One-group Posttest-onlyDesign Treatment Posttest Measure X O
  5. 5. One-group Pretest-Posttest Design A treatment condition is interjected between pre- and posttest of the dependent variable.Pretest measure Treatment Posttest Measure O X O Compare
  6. 6. Nonequivalent Posttest-Only Design  Performance of an experimental group is compared with that of a nonequivalent control group at posttest Posttest Treatment MeasureExperimental Group X O CompareControl Group O
  7. 7. Strong Experimental ResearchDesigns Designs that effectively control extraneous variables and provide strong evidence of cause and effect
  8. 8. Strong Experimental ResearchDesigns Basic designs – one IV and one DV  Between-participants  Within-Participants (repeated measures) Factorial Designs – multiple IVs
  9. 9. Posttest-Only Control Group Design  This design looks familiar, right?  What is different now? Posttest Treatment MeasureExperimental Group X O CompareControl Group O
  10. 10. Posttest-Only Control GroupDesign We could have more than 1 experimental group Posttest Treatment MeasureControl Group OExperimental Group 1 X1 O CompareExperimental Group 2 X2 O
  11. 11. Pretest-Posttest Control GroupDesign Simply add pretest to previous design What comparisons will we make? Pretest Posttest Treatment Measure Measure Experimental O X O Group Control O O Group
  12. 12. Benefits of Pretest Ensure equivalency of groups Detect ceiling and floor effects Empirically demonstrate effect of treatment See if initial position on DV is important
  13. 13. Within-Participants Designs A.k.a. repeated measures designs Most common: posttest-only P’s receive EVERY level of treatment Complete posttest after each exposure Will discuss counterbalancing next week There is no control group—each P is own control*
  14. 14.  Each participant experiences ALL conditions Example: impact of breakfast choice on test performance Eggs & NoPop-Tarts O O O toast breakfast P1 P1 P1 P1 P1 P1 P2 P2 P2 P2 P2 P2 P3 P3 P3 P3 P3 P3 P4 P4 P4 P4 P4 P4 P5 P5 P5 P5 P5 P5 Day 1 Day 2 Day 3
  15. 15. Advantages of within-participants Each P is his/her own control group Requires fewer P’s
  16. 16. Disadvantages of within-participants Sequencing effects  Order of condition exposure may impact DV  Counterbalancing helps Requires more time for each participant  Fatigue, attrition
  17. 17. Factorial Designs So far: basic designs (one IV, one DV) Now: more than one IV (still one DV)
  18. 18. 2 x 3 Factorial Design Independent Variable A A1 A2 A3 A1 B1 A2 B1 A3 B1 B1 B1 Cell mean Marginal meanIV B A1 B2 A2 B2 A3 B2 B2 B2 Marginal mean A1 A2 A3 Marginal Marginal Marginal mean mean mean
  19. 19. 2 types of effects Main Effect - The influence of one Independent variable in a factorial design Interaction Effect - joint influence of two or more IVs on the DV  The effect of one IV depends on the level of another IV.
  20. 20. Example Study examining gender (M-F) and intervention to improve test-taking skills 3 IV levels  control (no intervention)  reading material (instructional booklet)  personalized tutoring
  21. 21. Intervention Control Booklet Tutoring A1 B1 A2 B1 A3 B1 Male A1 B2 A2 B2 A3 B2Female
  22. 22. What would a main effect of genderlook like? 100 90 80 70 60 Male 50 Female 40 30 20 10 0 Control Reading Tutoring
  23. 23. What would a main effect ofintervention look like? 120 100 80 Male 60 Female 40 20 0 Control Reading Tutoring
  24. 24. What would an interaction looklike? 120 100 80 Male 60 Female 40 20 0 Control Reading Tutoring
  25. 25. What should we interpret? If one main effect - report it 2 main effects – report both BUT if there’s an interaction…  Only interpret/report the interaction  Because the effect of test-taking intervention depends on gender
  26. 26. Interaction 120 100 80 Male 60 Female 40 20 0 Control Reading Tutoring
  27. 27. Combining Between and WithinParticipant Designs Factorial design based on a mixed model -or- mixed model design IVs can be either between-groups (e.g., gender) or within-groups (a.k.a. repeated)
  28. 28. Advantages of FactorialDesigns Can test more than 1 hypothesis at a time Able to deal with extraneous variables  Build into design and test outright Increases precision b/c it evaluates more variables at once Allows researcher to understand interactive effects of variables
  29. 29. Disadvantages of Factorial Designs Gets messy with more than 2 IVs Requires more participants (N per cell) More difficulty to simultaneously manipulate all IVs when you have more of them
  30. 30. Choosing a Research Design Depends on… Research question Nature of variables you are investigating We have discussed design building blocks Page 255: guiding questions

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