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1. Experimental Designs Repeated (Related Measures), Independent Groups and Matched Pairs Design. 2. Learning Objectives <ul><li>Be able to explain the…
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  • 1. Experimental Designs Repeated (Related Measures), Independent Groups and Matched Pairs Design.
  • 2. Learning Objectives <ul><li>Be able to explain the different types of experimental designs. </li></ul><ul><li>Understand the strengths and limitations of different experimental designs. </li></ul>
  • 3. Recap: When planning experiments <ul><li>Independent and dependent variables need to be operationalised. </li></ul><ul><li>Hypotheses are one or two-tailed. </li></ul><ul><li>Extraneous variables need to be controlled or standardised. </li></ul><ul><li>Target population and sample size are decided. </li></ul><ul><li>Sampling technique is chosen. </li></ul><ul><li>Today : Design of study </li></ul>
  • 4. Experimental Design <ul><li>In an experiment we manipulate an IV. </li></ul><ul><li>There are usually two values of the IV e.g. </li></ul><ul><ul><li>Noise or no noise . </li></ul></ul><ul><li>These determine the conditions of the experiment. </li></ul><ul><li>Any experiment will have at least two conditions: an experimental and a control . </li></ul><ul><li>Organisation of participants across conditions can be arranged in several different ways. </li></ul>
  • 5. The R I M Designs <ul><li>R epeated Measures (Related Design) </li></ul><ul><li>I ndependent Groups </li></ul><ul><li>M atched Pairs </li></ul>
  • 6. R epeated Measures Design Recruit a group of participants Condition 1 Condition 2 The group does the experimental task with the IV set for condition 1 The group repeats the experimental task with the IV set for condition 2 Compare the results for the two conditions
  • 7. Strengths Limitations <ul><li>Any differences between conditions are likely to be due to changes in the IV and not due to participant variables. </li></ul><ul><li>Fewer participants need to be recruited, as they are used twice. </li></ul><ul><li>Order effects (e.g. practice effect, fatigue effect, recognising demand characteristics) as participants take part in all conditions. </li></ul>
  • 8. I ndependent Groups Design Recruit a group of participants Divide them into two This group does the experimental task with the IV set for condition 1 This group does the experimental task with the IV set for condition 2 Measure the DV for each group Compare the results for the two groups
  • 9. Strengths Limitations <ul><li>There are no order effects as participants only take part in one condition so cannot get better through practice, or under-performance due to fatigue, or change their behaviour due to demand characteristics. </li></ul><ul><li>It allows task variables to be controlled for example participants can be given the same word list in each condition so that this does not become a confounding variable. </li></ul><ul><li>Any differences between conditions could be due to individual differences in participants, for example one group could do better on recall because they are more motivated or more intelligent. </li></ul>
  • 10. M atched Pairs Design Recruit a group of participants Find out what sorts of people you have in the group Recruit another group that matches them one for one Condition 1 Condition 2 Treat the experiment as independent measures Compare the results for the matched pairs
  • 11. Strengths Limitations <ul><li>There are no order effects as participants only take part in one condition. </li></ul><ul><li>Individual differences between conditions are reduced as participants have been matched up. </li></ul><ul><li>It is time consuming and expensive to match up participants. </li></ul>
  • 12. Fatigue Effect, Boredom & Practice Effect <ul><li>Carrying out a task repeatedly leads to changes in performance </li></ul><ul><ul><li>Fatigue Effect: Deterioration of performance across conditions as PPs become tired or bored. </li></ul></ul><ul><ul><li>Practice Effect: Improvement across conditions through familiarity of the task or environment. </li></ul></ul><ul><li>This is a problem with repeated measures design </li></ul><ul><ul><li>Leave a long gap between conditions. </li></ul></ul><ul><ul><li>Use independent groups or matched pairs. </li></ul></ul><ul><ul><li>Counterbalanced design. </li></ul></ul>
  • 13. Counterbalancing <ul><li>Important control when using repeated measures </li></ul><ul><ul><li>Reduces ‘carry over’ effects </li></ul></ul><ul><ul><li>Half PPs do condition A then B </li></ul></ul><ul><ul><li>Other half do condition B then A </li></ul></ul><ul><li>Fully counterbalanced: ABBA </li></ul>
  • 14. Participant Variables <ul><li>Variation between PPs can affect DV </li></ul><ul><ul><li>Could mask an effect (accept null) </li></ul></ul><ul><ul><li>Could imply an effect where none exists (accept hypothesis) </li></ul></ul><ul><li>This is a problem with independent groups design </li></ul><ul><ul><li>Use repeated measures or matched pairs instead </li></ul></ul><ul><ul><li>Control by randomisation : random assignment to groups </li></ul></ul>
  • 15. Demand Characteristics <ul><li>Cues that the participants use to work out the experimental aim </li></ul><ul><li>They may alter their behaviour as a result either: </li></ul><ul><ul><li>(1) in line with expectation (pleasing the experimenter) </li></ul></ul><ul><ul><li>(2) away from expectation (’screw you’; Masling, 1966) </li></ul></ul>
  • 16. Sources of Demand Characteristics <ul><li>Poor research design decisions </li></ul><ul><ul><li>E.g. exposing PPs to knowledge of both conditions when it’s important they don’t know what the IV is </li></ul></ul><ul><li>Researcher behaviour/expectancy </li></ul><ul><ul><li>E.g. unintentional reinforcement of desired responses </li></ul></ul>
  • 17. Thank you for listening!
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