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14 Cards in this Set
- Front
- Back
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Repeated Measures Design also know as
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Within Subjects Design
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Repeated Measure Design
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Testing same group in which the group experiences all conditions including the control group.
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Why use Repeated Measure over Independent Group?
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-Lower number of subjects meaning easier to test on vulnerable populations and rare conditions
-More efficient -Higher sensitivity |
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Sensitivity
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-Ability to detect effect
-Ideally: participants respond similarly to manipulation -Realistically: Error Variance (variance in both subject and procedure) |
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As sensitivity ________ Variance ________
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Increases, Decreases
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Why run more than one participant in Repeated Measures?
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-Could be an outlier in the group
-Goal is to obtain generalizable results |
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Longitudinal Survey vs Repeated Measures
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-Repeated Measures has a control condition that surveys do not
-Longitudinal surveys desire to see change over time |
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Validity and Repeated Measures
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Practice Effect: the more times a subject is told to take the measures results may change
Interference Effect: Cognitive fatigue / boredom Carry-Over Effect: Analysis of first stimuli may effect how one analyzes the second or following tests Order Effect: what is presented first may change the results of the next (Dating and Quality of life study) An increased likelihood participants may catch on to the hypothesis |
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Counter Balancing
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Vary the order in which participants complete each condition
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Complete vs Incomplete Design
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Complete: All participants encounter all the conditions multiple times
Incomplete: Participants experience each condition once |
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Complete Design Counter Balance
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Block Randomization: used to order conditions for participants where size of block is equal to number of conditions. Reduces practice effect
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ABBA Counter Balancing
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Present conditions in one sequence (A->B) then present in opposite sequence (B->A) in order to see if practice effect is linear. MAY CREATE ANTICIPATION EFFECT
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Incomplete Design Counter Balance
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Selected Orders: use SOME of the practical orders
Latin Square:Each condition appears at ordinal position only once (constructed by taking # of conditions and using number as rows and columns) |
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Data Analysis of Repeated Measures
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2 conditions: use paired sample t test
2+ conditions: One way repeated measures ANOVA |