Factorial Designs

one-way experiments

single IV (2+ levels) 1 DV

Factorial Design

2+ IVs (factors) each w 2+ levels and 1 DV

interactions

when the effect of 1 IV depends on (varies as a function of) another IV

how many cells in a 2×2 factorial

4 cells

how many cells in a 2×4 factorial

8 cells

cell

1 condition of 1 variable in a factorial design

marginal mean

average score for 1 factor averaged across all levels of the other factor(s)

main effect

effect of 1 factor alone. found by looking at marginal means

interaction effect

difference in differences. shows as non-parallel lines on line graph

crossover interaction

direction of effect on one IV reverses as a function of level of other IV. lines intersect in an x

spreading/synergistic interaction

simple effects test

when you get a statistically significant interaction

between subjects/independent groups factorial design

individual experimental groups for each cell

within-groups factorial design

1 group experiences all cell conditions

mixed factorial design

one factor is manipulated as between-subjects and the other is within-groups

quasi-experiments

use subject predictor variables (can’t be manipulated but are systematically related to DV of interest) and sometimes factorial designs.