Transcript Chapter 11
A Within-Subjects Experiment: Homophone Priming of Proper Names Within-Subjects Factorial Designs Mixed Designs Advantages of Within-Subjects Designs Disadvantages of Within-Subjects Designs Controlling Within-Subjects Designs How Can You Choose a Design? What is a within-subjects design? In a within-subjects experiment, subjects are assigned to more than one treatment condition. Introduction Explain the statistical concept of power. Power is an experiment’s ability to detect the independent variable’s effect on the dependent variable. Introduction Why is statistical power desirable? Statistical power is desirable when it allows us to detect practically significant differences between the experimental conditions. Theoretically, there is a point of diminishing returns where excessive power detects meaningless differences between treatment conditions. Introduction Why is statistical power desirable? For example, in a study of treatments to lower blood pressure, a difference of 0.1 mm Hg— while statistically significant—would not affect patient health or life expectancy. Introduction Why do we call this approach a repeated-measures design? In a within-subjects experiment, researchers measure subjects on the dependent variable after each treatment. Introduction Summarize the basic principles of a within-subjects design. 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 Experiment What is a within-subjects factorial design? A within-subjects factorial design assigns subjects to all levels of two or more independent variables. Within-Subjects Factorial Designs What is a mixed design? A mixed design is an experiment where there is at least one between-subjects and one withinsubjects variable. Mixed Designs What are the advantages of within-subjects designs? Advantages: use fewer subjects save time on training greater statistical power more complete record of subjects’ performance Advantages of Within-Subjects Designs What are the disadvantages of within-subjects designs? Disadvantages: subjects participate longer resetting equipment may consume time treatment conditions may interfere with each other treatment order may confound results Disadvantages of Within-Subjects Designs When can’t we use a within-subjects design? We can’t use a within-subjects design when one treatment condition precludes another due to interference. Disadvantages of Within-Subjects Designs What is an order effect? Order effects are positive (practice) and negative (fatigue) performance changes due to a condition’s position in a series of treatments. The term, progressive error, encompasses both positive and negative order effects. Controlling Within-Subjects Designs How does counterbalancing control for order effects in within-subjects designs? Counterbalancing is a method of controlling order effects by distributing progressive error across different treatment conditions. Controlling Within-Subjects Designs How does counterbalancing control for order effects in within-subjects designs? Two major counterbalancing strategies are subject-by-subject counterbalancing, which controls progressive error for each subject, and across-subjects counterbalancing, which distributes progressive error across all subjects. Controlling Within-Subjects Designs What is a fatigue effect? A fatigue effect is form of progressive error where performance declines on the DV due to tiredness, boredom, or irritation. Controlling Within-Subjects Designs What are practice effects? Subject performance on the dependent variable may improve across the conditions of a withinsubjects experiment and these positive changes are called practice effects. Controlling Within-Subjects Designs What are practice effects? Practice effects may be due to relaxation, increased familiarity with the equipment or task, development of problem-solving strategies, or discovery of the purpose of the experiment. Controlling Within-Subjects Designs Why can’t we eliminate or hold order effects constant in a within-subjects experiment? We can’t eliminate order effects because there is an order as soon as we present two or more treatments. Holding order constant—always assigning subjects to the sequence ABC—would confound the experiment. Controlling Within-Subjects Designs What is the strategy of subject-by-subject counterbalancing? Subject-by-subject counterbalancing controls progressive error for each subject by presenting all treatment conditions more than once. Two subject-by-subject counterbalancing techniques are reverse counterbalancing and block randomization. Controlling Within-Subjects Designs How does reverse counterbalancing control progressive error? In reverse counterbalancing, we administer treatments twice in a mirror-image sequence, for example, ABBA. When progressive error is linear, it progressively changes across the experiment so that A and B have the same amount of progressive error. Controlling Within-Subjects Designs What is nonlinear progressive error? Nonlinear progressive error, which can be curvilinear (inverted-U) or nonomonotonic (changes direction), cannot be graphed as a straight line. Controlling Within-Subjects Designs Why can’t reverse counterbalancing control for this? Reverse counterbalancing only controls for linear progressive error. When progressive error increases in a straight line, this method actually confounds the experiment Controlling Within-Subjects Designs What is block randomization? Block randomization is a subject-by-subject counterbalancing technique where researchers assign each subject to several complete blocks of treatments. A block consists of a random sequence of all treatments, so that each block presents the treatments in a different order. Controlling Within-Subjects Designs What is a problem with subject-by-subject counterbalancing? Since subject-by-subject counterbalancing presents each treatment several times, this can result in long-duration, expensive, or boring procedures. This problem is compounded as the experimenter increases the number of treatments. Controlling Within-Subjects Designs What are our alternatives? Across-subjects counterbalancing techniques present each treatment once and controls progressive error by distributing it across all subjects. Two techniques are complete and partial counterbalancing. Controlling Within-Subjects Designs Explain complete counterbalancing. Complete counterbalancing uses all possible treatment sequences an equal number of times. Researchers randomly assign each subject to one of these sequences. Controlling Within-Subjects Designs Explain partial counterbalancing. Partial counterbalancing is a form of acrosssubjects counterbalancing, where we present only some of the possible (N!) orders. Two partial counterbalancing techniques are randomized partial and Latin square counterbalancing. Controlling Within-Subjects Designs When is a within-subjects superior to a betweensubjects design? A within-subjects design is usually preferable when you need to control large individual differences or have a small number of subjects. However, it may not be feasible if the experiment is long or there is a risk of asymmetrical carryover. How Can You Choose a Design?