11: factorial designs

goal of factorial designs

to test multiple things at once

levels of factorials

the options in a factor

factor

the subject/thing you want to test, the IV

what is a factorial design

research design that includes two or more factors (IVs)

number of conditions

the product of the number of levels of each factor

example of number of conditions

short vs long = 2 levels

passive vs active = 2 levels

=4

interaction effect

the effect that factor A has on the DV, depends on factor B

example of interaction effect

time spent on IG and it’s effect on mental health, changes based on how they use IG (passively or actively)

what is an interaction

the combined effects of the IVs

why is an interaction effect more important than a main effect

• less misleading. an interaction shows that it depends on the context

what is a main effect

tells you what one factor does by itself

purpose of a mixed design study

researcher can blenc different research strategies within one study

mixed design study

a factorial study that combines two different research designs

when to use mixed-design study

when one factor is expected to threaten validity

when to use higher order factorial designs

used for when designs involving 3 or more factors

how do higher order effects function

evaluate the main effects for each of the 3 factors

replication

repeating the previous study by using the same factor or IV as it was used in the previous study

expansion

adding a second factor in the form of new conditions or new participant characteristics

how to eliminate variance from individual differences in between-subjects

use a participant variable as a second factor to create a two-factor study

purpose of order effects as a second factor in a within subjects design

allows to evaluate any order effect that exist in the data, counterbalancing will help to do this