Chapter 11

• Within-Subjects Design


  A design in which each subject serves in more than one condition of the experiment
• Within-Subjects Design


  • Subjects serve in more than one condition of the experiment and are measured on the dependent variable after each treatment
  • Also known as a repeated-measures design
• Power


  The chance of detecting a genuine effect of the independent variable
• Within-Subjects Factorial Designs


  A factorial design in which subjects receive all conditions in the experiment
• Mixed Designs


  A factorial design that combines within and Between-Subjects variable in a single experiment
• Advantages of Within-Subjects Designs

  • Use the same subjects in different treatment conditions
  • Saves us time when we are actually running the experiment
  • It is more efficient to train each subject for several condition instead of just one
  • Chance of detecting the effect of our independent variable if we compare the behaviour of the same subjects under different conditions
• Disadvantages of Within-Subjects Designs

  • Require each subject to spend more time in the experiment
  • Subjects who are expected to perform many tasks might get restless during the experiment and begin to make hasty judgments to hurry the process along-leading to inaccurate data
• Interference Between Condition


  Taking part in more than one condition would be either impossible or useless or would change the effect of later treatments
• Order Effect


  Changes in subjects performance that occurs when a condition falls in different positions in a sequence of treatments
• Controlling for order effects

  Counterbalancing
• Fatigue effects


  Changes in performance cause by fatigue, boredom, or irritation
• Practice effects


  Changes in subjects performance resulting from practice
• Progressive error


  Changes in subjects responses that are caused by testing in multiple treatment conditions; includes order effects, such as the effects of practice or fatigue
• Counterbalancing


  A technique for controlling order effects by distributing progressive error across the different treatment conditions of the experiment; may also control Carryover effects
• Subject-by-subject Counterbalancing


  A technique for controlling progressive error for each individual subject by presenting all treatment conditions more than once
• Reverse Counterbalancing


  A technique for controlling progressive error for each individual subject by presenting all treatment conditions twice, first in one order then reverse order
• Block Randomization


  A process of Randomization that first creates treatment blocks containing one random order of the conditions in the experiments; subjects are then assigned to fill each successive treatment block
• Across-Subjects Counterbalancing


  A technique for controlling progressive error that pools all subjects data to equalise the effects of progressive error for each condition
• Complete Counterbalancing


  A technique for controlling progressive error using all possible sequences that can be formed out of the treatment conditions and using each sequence the same number of times
• Partial Counterbalancing


  Controls progressive error by using some subset of the available order sequences; these sequences are chosen through special procedures
• Randomised partial Counterbalancing


  The simplest partial counterbalancing; randomly selects as many sequences of treatment conditions as there are subjects for the experiment
• Latin square Counterbalancing


  A partial counterbalancing technique in which a matrix, or square, of sequences is constructed so that each treatment appears only once in any order position
• Carryover Effects


  The effects of some treatments will persist, or carry over, after the treatments/condition are removed or ends
• Balanced Latin square


  A partial counterbalancing technique for constructing a matrix, or square of sequences in which each treatment condition (1) appears only once in each position in a sequence and (2) precedes and follows every other condition an equal number of times