1. EXPERIMENTAL DESIGNS What Is Required for a True Experiment? What Are the Independent and Dependent Variables? What Is a Confounding Variable? What Are the Three Types of Experiments? What Can Reduce Internal Validity? How Does Counterbalancing Work? What Can Reduce External Validity?

2. What Is Required for a True Experiment? Cause – experimenter manipulates a variable Comparison – more than one condition Control – extraneous variables are eliminated or kept constant

3. What are the Independent and Dependent Variables? Independent Variable – variable manipulated by the experimenter Levels or conditions refer to the different values Dependent Variable – variable measured to assess the effect of the independent variable

4. What is a Confounding Variable? Variable other than IV and DV which changes between conditions Also called a “confound” When a potential confounding variable is controlled, it is called a control variable

5. What are the Three Types of Experiments? Between Subjects – Different subjects in each condition Matched Groups – Different subjects in each condition, but subjects are matched on one or more control variables Within Subjects – Same subjects in all conditions

6. What Can Reduce Internal Validity? Individual DifferencesDiffusion of Treatment HistoryDemand Characteristics MaturationExperimenter Effects InstrumentationFloor and Ceiling Effects AttritionRegression to the Mean Order Effects

7. Individual Differences Systematic differences between individuals in different groups Strategies – random assignment – matched groups – within subjects design

8. History Events outside the experiment Most likely when conditions are measured at different times with long delays Strategies – Decrease time between conditions – Add a control group measured at same times

9. Maturation Physical changes related to aging Particular problem for within-subjects designs Strategies – decrease time between measurements – add a control group measured at same times

10. Instrumentation Changes in the measuring instrument or equipment Strategy – Use standardized administration

11. Attrition Participants drop out of the study at different rates for the different conditions Strategies – Check attrition rates across groups – Compare participants who drop out to those who stay in

12. Diffusion of Treatment Information about the purpose of the study is shared with future participants Strategies – Short time span between participants – Use debriefing to request that participants do not share information about the study

13. Demand Characteristics Cues from the experimenter or research procedure about what behavior is desired Strategy – Single-blind procedure

14. Experimenter Effects Experimenter’s expectations affect measurements Strategy – Double-blind procedure

15. Floor and Ceiling Effects Measuring instrument is not sensitive enough – Floor effects – Ceiling effects Strategy – Check sensitivity of instrument prior to experiment

16. Regression to the Mean When measured twice, scores on the second testing tend to be closer to the mean Statistical phenomenon due to chance Strategy – Don’t select participants for groups based on extreme scores – Use an equivalently selected control group that does not get the treatment

17. Order Effects Also called Testing or Repeated Testing Effects of repeated measurements – Fatigue effects – Practice effects – Carryover effects Strategy – Counterbalance order of conditions

18. How Does Counterbalancing Work? Change the order of conditions Order effects will still exist but will affect all conditions equally This prevents order effects from being confounding

19. Complete Counterbalancing Each possible order of conditions is used for an equal number of subjects If your conditions are A,B, and C, 1/6 of participants will get each order: ABCCAB ACBCBA BACBCA

20. Latin Square Counterbalancing Each condition is presented in each position for an equal number of subjects Controls for practice and fatigue effects

21. Example Latin Square 1st 2nd 3rd 4th 1/4 get ABCD 1/4 get B C DA 1/4 get C DAB 1/4 get D ABC

22. Balanced Latin Square Latin square with additional requirement that each condition precedes and follows every other condition equally often Controls practice and fatigue effects Controls simple carryover effects (involving effect of a single condition)

23. Balanced Latin Square 1st 2nd 3rd 4th 1/4 get ABDC 1/4 get BCAD 1/4 get CDBA 1/4 get DACB

24. Randomized Counterbalancing Used when there are multiple stimuli tested for each condition Put the stimuli in random order for each participant

25. What Can Reduce External Validity? Unrepresentative Sample – use random or stratified random sampling – do exact or systematic replications Artificiality – use a more realistic setting – do systematic or conceptual replications