2.3 - Experimental Designs
Repeated measures design
Repeated measures design is a method used in psychological experiments where each participant experiences all conditions of the study.
Strengths of repeated measures design
- Fewer participants required - Since the same individuals are used for all conditions, the overall number of participants needed is lower compared to other designs.
- Control of individual differences - Using the same participants across conditions minimises the impact of personal variations on the results.
Weaknesses of repeated measures design
- Risk of boredom - Participants may lose interest or motivation when exposed to multiple conditions.
- Order effects - The sequence in which conditions are presented can influence outcomes, as participants might perform worse in later conditions.
- Practice effects - Repeated exposure to similar tasks can result in improved performance over time, which may skew results.
Independent measures design
Independent measures design involves assigning different groups of participants to each condition of the independent variable. This means that each individual only experiences one level of the variable being tested.
Advantages of independent measures design
- No risk of boredom or order effects - As participants only take part in one condition, there is no chance of fatigue, sequence bias, or familiarity affecting their performance.
- Elimination of practice effects - Since individuals are not exposed to repeated tasks, improvements due to prior experience are avoided.
Disadvantages of independent measures design
- Higher participant numbers needed - Different groups are required for each condition, increasing the total number of individuals needed.
- Impact of individual differences - Variations in personal characteristics between groups can influence the results, making it harder to isolate the effect of the independent variable.
Matched participants design
Matched participants design is a method where individuals are paired based on specific characteristics relevant to the study, with each member of the pair assigned to a different experimental condition.
Benefits of matched participants design
- Control over key variables - Participants are matched on important traits ensuring that these factors are evenly distributed across conditions. For instance, in Bandura's 1961 study, participants were matched on aggression levels, which was important for his study on the transmission of aggression.
Challenges of matched participants design
- Difficulty in finding matches - Identifying and recruiting enough participants who share the necessary characteristics can be time-consuming and may limit the sample size.
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