ANOVA (within-subjects) Flashcards
(11 cards)
Explained variance
Between-group differences
Explained variance indicates how much of the total variance is attributed to differences between groups in the study.
Unexplained variance
Within-groups (individual differences)
Unexplained variance reflects the variability among individuals within the same group.
3 sources of variance in repeated-measures ANOVA?
-Between conditions (effect)
-Between subjects (individual differences)
-Residual (error/noise)
These sources help to account for different types of variability in the data.
Advantage of repeated-measures ANOVA
Accounts for individual difference -> increased power
This means that repeated-measures designs can detect effects more easily due to controlling for variability among participants.
F-ratio
The F-ratio is a statistic used to determine if the explained variance is significantly greater than the unexplained variance.
Formula for MSunexplained
MSunexplained = MStotal - MSexplained - MSind diffs
This formula helps to isolate the residual variance after accounting for the explained variance.
What is counterbalancing in RM-ANOVA
Equal number of pps for all orderings
Counterbalancing helps to control for order effects by ensuring that all possible orders of conditions are represented equally.
SPSS procedure RM-ANOVA
-Analyse > general liner model > repeated measures
-Name factors and levels
-Assign variables to each level
Effect in multi-factorial ANOVA
-Main effect- one IV consistently affects DV
-Interaction effect- one IV’s effect depends on another IV
A main effect indicates that changes in one independent variable (IV) lead to changes in the dependent variable (DV), regardless of other IVs.
Challenge of interpreting higher-order factorial ANOVA
Interpretation of 3+ factor interactions is complex
As the number of factors increases, understanding the interactions becomes increasingly difficult.
Trade-off in higher-order factorial ANOVA
Between realism and interpretability
Real-world experiments may involve multiple IVs for realism, but this can complicate the analysis and interpretation of results.