Experimental designs

Experimental design

The different ways in which participants can be organised in relation to the experimental conditions

Independent groups deisgn

Participants are allocated to different groups where each group represents one experimental condition

Repeated measured.

All participants take part in all conditions of the experiments. Mean scores are compared to see if difference.

Matched pairs design

Pairs of participants are first matched on some variables that may affect the dependent variable. Then one member of the pair is assigned to condition A and the other to condition B.

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

Counter balancing.

An attempt to control for the effects of order in a repeated measures design. Half the participants experience the conditions in one order, and the other half in the opposite order.

Evalutation for independent groups

+No order effects, participants do one condition so no fatigue effects

+Less likely to guess aim, improves validity,

-Participants can confound results, differences between people may affect DV rather than IV

-Less economical, need more participants compared to repeated measures

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Evaluation for repeated measures

+Controls participant variables, same people in all conditions so differences are due to IV

+Fewer participants needed, more economical and quicker to recruit

+Higher internal validity (no individual differences between conditions

-Order effects (practise, fatigue, boredom ) can bias results.

-Participants may guess the aim more easily, demand characteristics

-Often requires counterbalancing to reduce order effects

Evaluation for matched pairs

+Reduces participant variables compared to independent groups

+Avoids most order effects because participants only do one condition

+Can improve validity compared to independent groups

-Time consuming and expensive to match participants

-Matching is never perfect, some differences still exist.

-Requires a pre test or prior data which can introduce issues.