Ch8: Between-subjects designs Flashcards
To how many levels of the IV are subjects in a between-subjects design exposed to?
ONE level of the IV
Forms of between-subjects designs
TWO GROUPS: -treatment and no treatment -two different levels -two different categories MULTIPLE GROUPS: -multiple levels of IV (including 0) -multiple categories
What are the advantages and disadvantages of between-subjects designs with 2 groups?
Pro:
-able to maximize differences between conditions (extreme ends of a continuum)
Con:
-not as much info can be obtained relative to multiple groups
Advantage/disadvantage of between-subjects designs with multiple groups?
Pro:
-greater understanding of relationship between variables due to more levels of the IV along continuum
Con:
-more difficult to find an effect
How would you determine significance in a 2 group between-subjects design with interval/ratio data?
independent sample t test.
Significance means groups 1 and 2 differ
How would you determine significance in a multiple-group between-subjects design with interval/ratio data?
ANOVA test.
Significance means there is a difference between groups, but it doesn’t tell you where the difference is.
A follow-up t test is then required
How would you determine significance in a between-subjects design with nominal/ordinal data?
Chi-squared test for proportions
Advantages of between-subjects designs
- sometimes you have no choice
- some research designs are logistically easier when using between-subjects design
- some variables can only be measures once
- individual score is independent from the other scores
- No contrast effects
- no fatigue effects
- no order effects (and other time-related effects)
Cons of between-subject designs
- individual differences between participants can become confounding variables. Greater risk of confounding variables
- require more participants
- individual differences can produce HIGH VARIABILITY in scores, making an effect harder to detect
- Threats to internal validity: selection of subjects, selection x maturation interaction, and mortality
Why is mortality a threat to internal validity in between-subject designs, but not in within-subject designs?
Because in a between-subject design, losing participants causes uneven conditions. In a within subject design, if a participant is lost, there aren’t people being lost in one condition more than another
Do you want MORE or LESS overlap for an effect higher in significance to be found?
LESS overlap for significant effect.
High variance within a treatment makes it harder to see effect
Define “contrast effects”
magnification or diminishment of perception as a result of previous exposure
threat to internal validity which involves bias in assigning participants to groups is called:
selection of subjects (mrS smith)
Different experimental groups would have grown apart regardless of IV. This threat to internal validity is known as:
selection x maturation interaction (mrs Smith)
Controlling for confounding variables:
- random assignment
- matching
- holding constant