Research Methods

1. Research Methods

2. 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

3. Experimental Methods • 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

4. Overview • 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

5. WHY REPEATED MEASURES • 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

6. PRACTICE EFFECTS • 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.

7. Complete Design • 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

8. Incomplete Design • 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

9. Orders selection • 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

10. DATA ANALYSIS • 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

11. Confirmation • 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

12. DIFFERENTIAL TRANSFER • 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

13. Repeated Measure Designs