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Published byBuddy Gregory Modified over 9 years ago
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Descriptive Methods ◦ Observation ◦ Survey Research Experimental Methods ◦ Independent Groups Designs ◦ Repeated Measures Designs ◦ Complex Designs Applied Research ◦ Single-Case Designs and Small-n Research ◦ Quasi-Experimental Designs and Program Evaluation
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OVERVIEW WHY RESEARCHERS USE REPEATED MEASURES DESIGNS THE ROLE OF PRACTICE EFFECTS IN REPEATED MEASURES DESIGNS ◦ Defining Practice Effects ◦ Balancing Practice Effects in the Complete Design ◦ Balancing Practice Effects in the Incomplete Design DATA ANALYSIS OF REPEATED MEASURES DESIGNS ◦ Describing the Results ◦ Confirming What the Results Reveal THE PROBLEM OF DIFFERENTIAL TRANSFER Repeated Measure Designs
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Repeated Measure Designs ◦ Within-subjects designs Subjects are repeatedly tested Each subject in all conditions Subjects as their own controls practice and fatigue effects ◦ Improvement with practice ◦ Worse with fatigue/reduced motivation No elimination but balancing ◦ Averaged across the conditions
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Conduct experiment with few participants ◦ Special populations (individuals with brain injuries) Conduct experiment more efficiently Increase sensitivity ◦ Ability to detect the effect ◦ Minimize error variation Study changes in behavior over time
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Same individuals in each condition: ◦ No confounding on individual differences variables Practice effects: Change because of repeated testing (not because of the independent variable) Practice effects = threat to internal validity ◦ If different conditions are presented in the same order to all participants Two types of RMD (complete and incomplete) ◦ Differ in the ways to control for practice effects.
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Block randomization ◦ Random order of all condition on each presentation ◦ Blocks = No of administrations of each condition (Tr/Cd) ◦ Blocks Size = Number of conditions ◦ Balancing = Avg presentation of each condition shall be equal ◦ Avg Pc = Σ (cd number) / Blocks ABBA counterbalancing ◦ Random sequence followed by opposite sequence ◦ Suitable for small number of conditions and trials ◦ Balancing = 2 trials Non-linear practice effects or Anticipation effects ◦ Block randomization >> ABBA
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Balanced across subjects Each condition in each ordinal position ◦ Orders = N! ◦ N=Conditions ◦ Participants = Any Multiple of all Possible Orders <=4 conditions : Use all possible orders Random Assignment Methods for orders selection ◦ Latin Square and Random starting order with rotation ◦ Orders = Any Multiple of Conditions
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Latin Square ◦ each condition at each ordinal positions once ◦ each condition precedes and follows each other condition exactly once Random starting order with rotation ◦ Begin with a random order ◦ Rotate sequence systematically
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Errors and outliers (data scanning) A summary score (e.g., mean, median) ◦ Each participant (incomplete design) ◦ Each participant in each conditions (complete design) Descriptive statistics ◦ Performance across all participants ◦ For each condition of IV
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Probability testing Same as in random group design ◦ Null hypothesis testing ◦ Confidence interval Error variation ◦ More sensitive ◦ Not cause of individual differences ◦ Difference in ways the conditions effect the results
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Persistence of effects of one condition Influence performance in subsequent conditions Common with instructional variables ◦ Threat to internal validity of RMD Identification of DT ◦ Same variables in RMD and RGD Use RGD
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