1. CHAPTER 6 Control Problems in Experimental Research

2. Chapter 6. Control Problems in Experimental Research Chapter Objectives Distinguish between-subjects designs from within- subjects designs Understand how random assignment can solve the equivalent groups problem in between-subjects designs Understand when matched random assignment should be used when attempting to create independent groups

3. Chapter Objectives Distinguish between progressive and carry-over effects in within-subjects designs Describe the various forms of counterbalancing Describe the specific types of between- and within-subjects designs that occur in developmental psychology, and understand the problems associated with each Describe how participant/experimenter bias can occur and how it can be controlled

4. Between-Subjects Designs Comparison is between two different groups of subjects (each subject receives one level of IV) Necessary when Subjects in each condition have to be naïve Barbara Helm study Subject variable (e.g., gender) is the IV Main problem to solve: creating equivalent groups

5. Creating Equivalent Groups Random assignment Each subject has equal chance of being assigned to any group in the study Spreads potential confounds equally through all groups Accomplished through blocked random assignment

7. Creating Equivalent Groups Random assignment Each subject has equal chance of being assigned to any group in the study Spreads potential confounds equally through all groups Accomplished through blocked random assignment Matching Deliberate control over a potential confound Use when Small N per group might foil random assignment Some matching variable correlates with DV Measuring the matching variable is feasible

8. Within-Subjects Designs Also called repeated-measures designs (same subjects in every level of an IV) Comparison is within the same group of subjects Used when comparisons within the same individual are essential (e.g., perception studies) Removes possibility that differences between levels of the IV due to individual differences Level 1Level 2

9. Within-Subjects Designs Main problem to solve  order effects Progressive Carry-over (harder to control) Sequence A-B may yield differ carryover than the sequence B-A

10. Controlling Order Effects Counterbalancing Altering the order of the experimental conditions Complete counterbalancing (all possible orders = x!) Test participants in every possible different order at least once Works well with only a few conditions Partial counterbalancing Random sample of all possible combinations is selected Notice: Skip p219 “Testing more than once per condition” to end of p 223.

11. Methodological Control in Developmental Research Cross-sectional design Between-subjects design Potential for cohort effects Worse with large age differences Longitudinal design Within-subjects design Potential for attrition difficulties Cohort sequential design Combines cross-sectional and longitudinal

12. Problems with Biasing Experimenter bias Experimenter expectations can influence subject behavior Controlling for experimenter bias Automating the procedure Using a double blind procedure

13. Problems with Biasing Subject bias Hawthorne effect: Effect of knowing one is in a study “ Good” subjects Participants tend to be cooperative, to please the researcher Evaluation apprehension Participants tend to behave in ideal ways so as not to be evaluated negatively Demand characteristics Cues giving away true purpose and study’s hypothesis Controlling for participant bias Effective deception Use of manipulation checks Field research

14. Ethical Responsibilities of Participants Be responsible Show up for scheduled appointments, or inform research of cancellation Be cooperative Behave professionally when participating in research Listen carefully Ask questions if unsure of your rights or of what you are asked to do Respect the researcher Do not discuss study with others Be actively involved in debriefing Help the researcher understand your experience

15. Lab Prep Stroop Effect John Ridley Stroop (1935) RED GREEN BLUE YELLOW 1 2 3

16. Lab Prep Stroop Effect Modern-day Stroop Paradigm RED GREEN BLUE YELLOW congruent incongruent RED GREEN BLUE YELLOW Automaticity Relative Speed of Processing (“horse-race” model)

17. “Horse-Race” Model When two processes occur in parallel, the faster one May interfere with the slower one, but not vice versa. RED “red”

18. “Horse-Race” Model When two processes occur in parallel, the faster one May interfere with the slower one, but not vice versa. RED “red”

19. Is the “Horse-Race” Model Supported? CongruentIncongruent Name color Read word What would the horse race model predict? If prediction turns out to be true, we support the model.