CHAPTER 11: WITHIN-SUBJECTS DESIGNS

• Across-subjects


  A technique for controlling progressive error that pools all subject's data together to equalize the effects of progressive error for each condition
• Counterbalancing


  A technique for controlling order effects by distributing progressive error across the different treatment conditions of the experiment; may also control carryover effects
• Balanced Latin Square


  A partial counterbalancing technique for constructing a matrix, or square, of a 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
• Block Randomization


  A process of randomization that first creates treatment blocks containing one random order of the conditions in the experiment; subjects are then assigned to fill each successive treatment block
• Carryover Effects


  The persistence of the effect of a treatment condition after the condition ends
• 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
• Fatigue Effects


  Changes in performance caused by fatigue, boredom, or irritation
• 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
• Mixed Design


  A factorial designs that combines within-subjects and between-subjects factors
• Order Effects


  Change in subjects' performance that occurs when a conditions falls in different positions in a sequence of treatment
• Partial Counterbalancing


  A technique for controlling progressive error by using some subset of the available sequences of treatment conditions
• Power


  The chances of detecting genuine effect of the independent variable
• Practice Effect


  Change 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
• Randomized Partial Counterbalancing


  The simplest partial counterbalancing procedure in which the experimenter randomly selects as many sequences of treatment conditions as there are subjects for the experiment
• Reverse Counterbalancing


  A technique for controlling progressive error for each individual subject by presenting all treatment conditions twice, first in one order, then in the reverse order
• Subject-by-subject Counterbalancing


  A technique for controlling progressive error for each individual subject by presenting all treatment conditions more than once
• Within-subjects Design


  A design in which each subject takes part in more than one condition of the experiment; also called a repeated-measures design
• Within-subjects Factorial Design


  A factorial design in which subjects receive all conditions in the experiment
• Power is an experiment's ability to detect the independent variable's effect on the dependent variable
• Statistical Power is desirable when it allows us to detect practically significant differences between the experimental conditions
• In a within-subjects experiment, researchers measured subjects on the dependent variable after each treatment
• Subjects participate in more than one treatment condition and serve as their own control
• We compare their performance on the dependent variable across conditions to determine whether there is a treatment effect
• A within-subjects factorial design assigns subjects to all levels of two or more independent variables
• A mixed design is an experiment where there is at least one between-subjects and one within subjects variable
• Order effects


  Positive (practice) and negative (fatigue) performance changes due to a condition's position in a series of treatments
• Fatigue Effects


  A form of progressive error where performance declines on the DV due to tiredness, boredom, or irritation
• Practice Effects


  Positive changes in subject performance across the conditions of a within-subjects experiment
• Progressive Error


  Changes in the subjects response that are caused by testing in multiple treatment conditions
• Counterbalancing


  A method of controlling order effects by distributing progressive error across different treatment conditions
• Block Randomization


  A subject-by-subject counterbalancing technique where researchers assign each subject to several complete blocks of treatments
• Across-subject Counterbalancing


  Techniques that present each treatment once and control progressive error by distributing it across all subjects
• Complete Counterbalancing


  It uses all possible treatment sequences an equal number of times
• Partial Counterbalancing


  A form of across-subjects counterbalancing, where we present only some of the possible (N!) orders
• Randomized Partial Counterbalancing


  The simplest partial counterbalancing procedure where we randomly select out as many sequences as we have subjects for the experiment
• Latin Square Counterbalancing


  A matrix, or square, of sequences is constructed that satisfies the following conditions: Each treatments appears only once in any order position in the sequences
• Carryover Effects


  The effects of some treatments will persist, or carry over, after the treatments are removed
• Balanced Latin Square


  Each treatment condition (1) appears only one once in each position in the order sequences and (2) precedes and follows each other condition and equal number of times