Experimental design

• types of experimental designs

  • Independent groups design
  • Repeated measures design
  • Matched pairs design
• Independent groups design


  An experimental design where each participants only takes part in one condition of the IV
• Matched pairs design


  An experimental design where pairs of participants are matched on important characteristics and one member allocated to each condition of the IV
• Repeated measures design


  An experimental design where each participants takes part in all conditions of the IV
• Strengths: Independent groups design

  • Order effects cannot be observed, as no participants will be used in more than one condition
  • Data collection will be less time-consuming if all conditions of the experiment can be conducted simultaneously
• Limitations: Independent groups design

  • Different participants need to be recruited for each condition, which can be difficult and expensive
  • There is a risk of participant variables affecting the results between conditions, rather than solely manipulation of the independent variable
• Strengths: Matched pairs design

  • Order effects will not be observed as participants only take part in one condition
  • The tailored participant-matching process reduces the risk of participant variables from affecting results between conditions
• Limitations: Matched pairs design

  • Different participants need to be recruited for each condition, which is difficult and expensive
  • Matching is a more complex process, and it will always be very difficult to match participants identically
• Strengths: Repeated measures design

  • The results will not be subject to participant variables putting more confidence in dependent variable changes being solely due to manipulated changes in the independent variable
  • As the same participants are used at least twice, extra participants do not need to be recruited
• Limitations: Repeated measures design

  • There is risk of observing order effects
  • If a participant drops out, data will be lost from all conditions of the experiment rather than one
• How can you reduce the risk of order effects in a repeated measures design

  • counterbalancing
  • controlling the order of variables so that each order combination occurs the same number of times, e.g. one half of participants partake in condition A followed by B, whereas the other half partake in B followed by A