Research Methods- Experimental Design Flashcards
Repeated measures design:
The same participants complete the two levels (or more) of the independent variable.
Independent groups design:
Different participants complete the two levels (or more) of the independent variable.
DETAILED
Independent groups design:
Different participants complete in each of the two (or more) conditions of the experiment. Participants are randomly allocated to each condition (to avoid researcher bias when assigning to conditions).
What type of data does independent group design produce?
Produces unrelated data, the individual data points in one condition cannot be paired with any of the data points in the other condition.
Evaluation
Independent group design
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Participant variables: If more participants with a particular characteristic are randomly assigned to one of the groups (e.g. age), This can influence the measurement of the DV (an extraneous variable)
DETAILED
Repeated measures design
The same participants complete in each of the two (or more) experimental conditions
What type of data does Repeated measures design produce?
Produces related data, each participants score (data point) in one condition can be paired with a data point (their own score) in the other condition.
Evaluation
Repeated measures design
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Order effects: Taking part in the first condition influences performance in the second condition. E.g. worsen due to fatigue or boredom, or improve due to practice. Participants are more likely to figure out the aim and alter behaviour due to demand characteristics.
What controls order effects?
Counter balancing attempts to control for (does not eliminate) order effects. This uses ABBA format, half the participants complete condition A first and B second, the other half of the sample start with condition B then A
IGD
ADVANTAGES
• Participants are less likely to work out the aim than RMD as they only take part in one condition, meaning reduced demand characteristics.
• No order effects as participants only take part in one condition
IGD
DISADVANTAGES
• IGD needs double the participants compared to RMD for the same amount of data.
• Participant variables between the conditions is a problem as the participants take part in only one condition.
RMD
ADVANTAGES
• RMD needs half the participants compared for IGD for the same amount of data.
• Participant variables between the conditions is not a problem as the participants take part in both conditions.
RMD
DISADVANTAGES
-Participants are more likely to work out the aim than in IGD as they take part in both conditions meaning increased demand characteristics.
-Order effects, participant performance can improve or worsen between the conditions due to factors like practice and fatigue.
Matched pairs design:
Different participants complete in each of the two (or more) conditions of the experiment. Participants are first assessed and ranked on a characteristic (e.g. aggression) and then the top two participants (then each following two are randomly assigned to separate conditions.
What type of data does Matched pairs design produce?
Produces related data, Each participants score (data point) in one condition can be paired with a data point (the participant matched to them) in the other condition.
