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# Chapter 11 Human Participants Review - PowerPoint PPT Presentation

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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### Chapter 11Human Participants Review

Wednesday, July 16

• 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

• 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

• 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

• 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)

• 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

• 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

• 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

• 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

• 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

• 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

• 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)