Experimental design Flashcards
Experimental design
The different ways in which the participants are assigned to different groups/conditions of the experiment – independent groups, repeated measures or matched pairs.
Independant groups
Participants are allocated to different groups where each group represents one experimental condition. The participants are randomly allocated into each group.
Matched pairs
Pairs of participants are first matched on some variable(s) that may affect the dependent variable. Then one member of the pair is randomly assigned to Condition A and the other to condition B.
Repeated measures
All participants take part in all conditions of the experiment.
Random allocation
An attempt to control for participant variables in an independent groups design which ensures that each participant has the same chance of being in one condition as any other.
Counterbalancing
An attempt to control for the effects of order in a repeated measures design: half the participants experience the conditions in one order, the other half in the opposite order.
Independent group strength
Order effects are not a problem whereas they are a problem for repeated measures.
Participants are less likely to guess the aims which reduces demand characteristics.
Independent group weakness
The partcipants who occupy the different groups are not the same in terms of participant variables. This can be overcome using random allocation of groups.
They are less economical than repeated measures as twice as many participants would be needed to produce equivalent data.
Repeated Measures strengths
The participant variable are controlled therefore there is a higher validity.
Fewer participants are needed therefore less time is spent recruiting them.
Repeated Measures weaknesses
Each participant has to do at least two tasks and the order of these tasks may be significant so order effects may arise.
It is more likely the participants will work out the aim of the study when they experience all conditions of the study so demand characteristics feature more.
Matched pairs strengths
Participant variables are significantly lessened as they are matched up on the variables.
Participants only take part in a single condition so order effects and demand characteristics are less of a problem.
Matched pairs weaknesses
Participants can never be matched exactly so there will always be important differences between ppts which may affect the DV.
Matching may be time-consuming and expensive, particularly if a pre-test is required so it is the least economical of the designs.
