Ch. 12- Mixed Design Flashcards
Meta Analysis:
Quantitative statistical analysis that combines the results of individual but similar studies
Single Subject Design
• Special types of within subjects design
• Uses one participant or group to assess changes within that individual or group
• Also called a single-case experimental design, single-n design
Participant serves as their own control
A-B Design
Researchers take a baseline measurement (Phase A) and then introduces the intervention, and measures that same variable again (Phase B)
A-B-A design
○ Baseline, intervention, remove intervention and measure variable again
Helps establish covariation by showing that behaviour systemically changes as researches introduce and remove the treatment
A-B-A-B Design
Baseline, intervention, remove intervention, reintroduce intervention
2 Group
Between
Pre/Post Test
Within
MultiGroup
Between
Factorial
Between
Repeated Measure
Within
Mixed
Between and Within
Between Subject
Expose participants to 1 level of treatment
Randomly assign participants to one condition
High Internal and external validity
Low Power
Within Subject
Expose participants to all levels of treatment
Randomly assign as sequence of treatment conditions
High Power
Low Internal and external validity
Waiting List Control Group:
- Empty control group often used in clinical research
- Participants do not receive treatment or intervention until after the completion of study
After determining best form of intervention, participants receive the better treatment at no cost
Experimenter-Expectancy Effect:
• Bias causes a researcher to unconsciously influence the participants of an experiment
Also called expectancy bias, experimenter effect
Double Bind Procedure:
• In order to reduce the likelihood that expectancies or knowledge of condition will influence the results
Both the participants and administrators are unaware of the types of treatment being provided
Single Blind Procedure:
• Participants are unaware of the treatment they are receiving
Administrator knows
Mixed Design ANOVA
• Tests for difference between 2 or more categorical independent variable
One is between subjects variable, another is within subjects available
Mixed ANOVA- Df
3 degrees of freedom
1 for between, within, and interaction
Mixed ANOVE- F statistic
1 for main effect, 1 for interaction
Size of difference between condition means compared to size of residual error
Eta^2
○ Effect size
Proportion of change in the dependent variable that is associated with being in the different groups of the independent variable or the interaction of independent variable
