Chapter 9: Within Subjects Design Flashcards
How to calculate the F ratio for a Within Subjects design?
F=(condition effects+error)/error
What are the threats to internal validity in a within subjects design?
Confounding environmental variables
Def→ Any characteristic in the environment that may differ between treatment conditions
- ex: lightning, noises
- may cause differences in score between two conditions
- may lead to a confound
Can control it by
- Standardizing it→ holding constant the environment
- Matching across conditions
- Randomization
Confounding time-related factors->Big 5
- History, Maturation, Instrumentation, Regression toward the mean, Testing effects
What are the two types of testing effects?
- carryover effects→ one manipulation produce persistent consequences influencing the participants’ response to subsequent manipulations
- progressive error→ Changes to behaviour/performance that are related to general experience in research study (practice effects and fatigue effects)
What are the different types of counterbalancing?
Complete counterbalancing→ All possible treatment orders are used equally often
- N!→ 3! = 1x2x3= 6 possibilities
- must be equal numbers of participants in each counterbalanced order
—>don’t eliminate order effects BUT control for them
Latin-Square Counterbalancing
Each condition occurs equally often in each order in the experiment
- don’t need all possibilities BUT simply make sure that each conditions occurs once in each order
- ex: ABC, BCA, CAB → only need 3 order instead of 6 possible orders
Partial counterbalancing
Each condition is preceded and succeeded equally often by the same conditions
- ex→ Condition A is preceded by Condition D and is succeeded by Condition B
What are the advantages of a within subjects design?
Need fewer participants
Eliminates problems of individuals differences
Increase chances of detecting treatment effect
What are the disadvantages of a within subjects design?
Not suitable when carry-over effects are expected
Participant attrition might be a problem
- change sample size and exaggerate volunteer bias
Ordering of conditions can be time-consuming and require many participants
- does not eliminate order effects