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Chapter 11 Human Participants Review

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Chapter 11 Human Participants Review. Wednesday, July 16. Single-variable, Correlated-Groups Designs. Introduces a correlation between groups in the way groups are formed Within-subjects design: Same participants in each group Matched-groups design Groups formed by matched random assignment.

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single variable correlated groups designs
Single-variable, Correlated-Groups Designs
  • Introduces a correlation between groups in the way groups are formed
    • Within-subjects design:
      • Same participants in each group
    • Matched-groups design
      • Groups formed by matched random assignment
correlated groups designs
Correlated-Groups Designs
  • More sensitive than independent-groups designs
    • Controlling for individual differences makes it easier to detect small effects
  • The existence of a correlation between conditions has important implications for design and analysis
within subjects designs
Within-Subjects Designs
  • All participants are exposed to all experimental conditions
  • Each participant serves as “his or her own control”
  • In this way individual differences are removed from the treatment effect
within subjects designs5
Within-Subjects Designs
  • Need to control for sequence effects
    • Sequence effects result from the experience with one condition affecting the performance in subsequent conditions
    • Controlled by varying the order of presentation (such as with counterbalancing)
statistical analysis
Statistical Analysis
  • Appropriate Statistical Analyses
    • Correlated t-test (for 2 groups only)
    • Repeated measures ANOVA
  • Order data so that each line represents one participant and each row represents one condition
    • Note that the columns represent conditions, NOT the order of testing
within subjects strengths
Within-Subjects Strengths
  • More sensitive to small group differences because the variability due to individual differences is statistically eliminated
  • Fewer participants are needed because each participant appears in each condition
  • Instructions may take less time because participants were already instructed on the task in previous conditions
within subjects weaknesses
Within-Subjects Weaknesses
  • Because participants experience all conditions, they may figure out the hypothesis (potential subject effects)
  • Major issue is sequence effects
    • Practice and carry-over effects
    • Controlled by varying the order of presentation
      • Counterbalancing
      • Random order of presentation
      • Latin square design
matched subjects designs
Matched-Subjects Designs
  • Introduces correlation by matching the participants in each group with participants from the other groups
  • Should match on “relevant” variables
    • Variables that affect the dependent variable
    • Variables that show considerable natural variation in the population sampled
matching participants
Matching Participants
  • Match participants in sets, where the size of the set is equal to the number of conditions
  • Matching gets more difficult as:
    • The number of matching variables increases
    • Matching is done on continuous variables
    • The number of conditions increase
  • Once sets are matched, you randomly assign the participants in the set to the conditions
statistical analysis11
Statistical Analysis
  • Analyze as if it were a within-subjects study
    • Data from matched participants are organized as if the data came from a single participant
  • Tell the program that the number of participants was equal to the actual number of participants divided by the number of conditions
    • e.g., for 40 participants and 4 conditions, tell the program that you had 10 participants and 4 conditions in a within-subjects design
strengths and weaknesses
Strengths and Weaknesses
  • Strengths
    • Increased sensitivity to small differences between groups,but without the sequence effects of within-subjects designs
  • Weaknesses
    • Extra work of matching participants
    • Participants without appropriate matches cannot be used in the study
  • Can introduce a correlation in two ways
    • Within-subjects designs
    • Matched-subjects designs
  • These designs are more sensitive to small differences between groups
  • The costs for the greater sensitivity are:
    • Sequence effects (within-subjects design)
    • Matching difficulties (matched-subjects design)