WEEK 14

• Within-Subjects Designs

  Small N
• Historical context

  • 1800's to early 1900's - Wundt, Pavlov based on observation
  • 1920's - 1960's - Ronald Fisher, ANOVA, Control / Experimental groups
  • 1950's onwards - Small N & Large N
• N

  Number of participants
• Difference between Large N and Small N Design

  • Large N: Participants are grouped, Data from individual participant's not main interest, Data from each group are studied, Data are represented as group averages, Data are analyzed with statistics
  • Small N: Each participant is a separate experiment, Almost always repeated-measures designs, Researchers observe how the subject responds in several conditions, Individual Data are presented (Not averaged), Data are analyzed with visual inspection

  
• Characteristics of Small N designs

  • Baseline phase - generally measures behavior without any treatment
  • Intervention phase- measures behavior once a treatment is applied
  • Individual data are compared across baseline and intervention phases
• Discrete trials design

  Does not rely on baselines; instead, it relies on presenting and averaging across many applications of different treatment conditions and comparing performance on the DV across the treatment conditions; repeated presentation over many trials can show reliable effects of the IV
• A discrete trials design is a small N design without baselines
• Advantage of Discrete trials design

  • You get a more accurate picture of results or effects (because you measure the effects multiple times and observe it closer)
• Disadvantage of Discrete trials design

  • Making multiple observations is time consuming and tedious
• Small N design is often used to test the effects of positive or negative reinforcement on individuals with behavioral problems; Animal researchers prefer small N designs to minimize the acquisition and maintenance cost, training time, and possible sacrifice of their animal subjects
• When are small N designs useful?