4. Experimental Designs

• 1. Experimental Designs

  • how participants organised in diff. types of experiment conditions.
  • the way 2 levels of IV delivered.
• 2. Experimental Designs - IGD

  Independent Group Designs (IGD):

  • separate participants experience 2 diff conditions (only does one).
  • tested against e/o = comparison.
• 2a. Experimental Designs - IGD

  IGD - Strengths:

  • no orders effect (order not effect outcome).
  • lower demand c (less chance guessing).
• 2b. Experimental Designs - IGD

  IGD - Limitations:

  • participants not same in terms of participant variables - if find mean difference between groups on DV, may be due to variables not IV (cofounding variables = low validity).
  • less economical - more participants needed, more money/time spent.
• 3. Experimental Designs - RMD

  Repeated Measures Design (RMD):

  • each participant tested in all conditions.
  • tested against themselves = comparison.
• 3a. Experimental Designs - RMD

  RMD - Strengths:

  • participant variables controlled = higher validity.
  • more data, less participants needed (economical).
• 3b. Experimental Designs - RMD

  RMD - Limitations:

  • orders effect - first task may effect other one and/or boredom/fatigue effects performance = cofounding variables.
  • demand c - both conditions, so easier to guess.
• 4. Experimental Designs - MPD

  Matched Pairs Design (MPD):

  • matched on characteristics relevant to experiment (e.g. IQ).
  • one member from each pair in one condition, other in other condition.
  • MZ/DZ twins often used.
• 4a. Experimental Designs - MPD

  MPD - Strengths:

  • lowers demand c (less chance guessing).
  • no orders effect.
  • group difference (some extent).
• 4b. Experimental Designs - MPD

  MPD - Limitations:

  • can’t be matched exactly/perfectly = affect DV.
  • less economical - more participants needed, time consuming.
• 5. Experimental Designs - Counterbalancing

  Counterbalancing:

  • attempt control orders effect (RMD).
  • 1/2 in con A, then B while other 1/2 B, then A.
  • doesn‘t remove orders effect, balances effect between 2 conditions.
• 6. Experimental Designs - Random Allocation

  Random Allocation:

  • attempts control effects of participant variables (IGD), ensuring participants have same chance in one condition as other.
  • decrease systematic error, individual differences in response/ability less likely affect results.
• 7. Experimental Designs - Standardisation

  Standardisation:

  • procedures used kept the same.
  • effort keep elements identical = changes in data linked to IV.
• 8. Experimental Designs - Dealing w/ Issues

  IGD:

  • random allocation distributes participant variables.
• 8a. Experimental Designs - Dealing w/ Issues

  RMD:

  • 2 diff tests to practice (order effects).
  • counterbalancing.
  • fake details give to conceal purpose (lower demand c).
• 8b. Experimental Designs - Dealing w/ Issues

  MPD:

  • restrict number variables participants matched on.
  • identify most important variables in pilot study.