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Chapter 9

Chapter 9 notes

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Chapter IX: Experimental Designs Within Subjects Design 9.1 Research Strategies • The defining characteristic of a between-subjects experiment is that it requires separate but equivalent groups of participants for the different treatment conditions compared. • Alternative research procedure: the within –subjects design • The defining characteristic of a within-subjects design is that it uses a single group of participants, and tests or observes each individual in all of the different treatments being compared. • The sample is not separated into several groups but rather exists as a single group that participated in every treatment condition In a within-subjects design the same group of individuals participated in every level of the independent variable so that each participant experiences all of the different levels of the independent variable. • In one sense, a within-subjects study is the ultimate in equivalent groups because the group in one treatment condition is absolutely identical to the group in every other condition. In the context of statistical analysis, a within-subjects design is often called a repeated-measures design because the research study repeats measurements of the same individuals under different conditions. • Within-subjects design may be used in investigations of changes over time. • Figure 9.1 [The Structure of a Within-Subjects Design] The same sample of individuals participates in all of the treatment conditions. Because each participant is measured in each treatment, this design is sometimes called a repeated-measures design. Note: all participants go through the entire series of treatments but not necessarily in the same order. A within-subjects experimental design, also known as a repeated measures experimental design, compares two or more different treatment conditions (or compares treatment and control) by observing or measuring the same group of individuals in all of the treatment conditions being compared. Thus, a within-subjects design looks for differences between treatment conditions within the same group of participants. To qualify as an experiment, the design must satisfy all other requirements of the experimental research strategy such as manipulation of an independent variable and control of extraneous variables. • One advantage of a within-subjects design is that it requires relatively few participants in comparison to between subjects designs. • The primary advantage of a within-subjects design, however, is that it essentially eliminates all of the problems based on individual differences that are the primary concern of a between-subjects design. • There are no individual differences to confound the study. • Each participant appears in every treatment condition, each individual serves as his own control or baseline. • In a within-subjects design, it is possible to measure the differences between treatments without involving any individual differences. • Because the same participants are in every treatment condition, the treatment effects and the individual differences are not linked. • In a within-subjects design, it is possible to measure the differences between individuals. When the individual differences are consistent across treatments, they can be measured and removed from the rest of the variance in the data. • By measuring and removing individual differences, the within-subjects design reduces variance and reveals treatment effects that might not be apparent in a between-subjects design. • A within-subjects design is more likely to detect a treatment effect than a between- subjects design. • The primary disadvantage comes from the fact that each participant goes through a series of treatment conditions with each treatment administered at a different time. • Errors introduced based on time-related factors, such as fatigue or the weather • Another potential problem for the within-subjects design is participant attrition – people who start the research study may be gone before the study is completed • To note, because a within-subjects design requires repeated measurements under different conditions for each individual, some participants may be lost between the first measurement and the final measurement • Participants may forget appointments, lose interest, quit, move away, or even die. • The attrition problem may exaggerate volunteer bias 9i.e. dedicated volunteer) – may threaten external validity 9.2 Threats To Internal Validity For Within-Subjects Designs • Confounding from environmental variables. Environmental variables are characteristics of the environment that may change from one treatment condition to another. • Examples: [morning, afternoon, night] or [room 1 and room 2] • Confounding from time-related factors. A serious concern of within-subjects designs comes from the fact that the design requires a series of measurements made over time. History. Scores may be affected by changing events outside the study. Maturation. Scores may be affected by physiological or psychological changes in participants. Instrumentation. Scores may be affected by changes in the measuring instrument. Testing effects. Scores may be affected by experience in prior treatment conditions. Regression. Extreme scores may become less extreme due to statistical regression. • Testing effects are directly related to experience obtained by participating and being measured in previous treatment conditions • Testing effects are often called order effects. Those are in place to emphasize that the participants go through a series of treatments in order, and that performance in any treatment may be influenced by treatments that occurred earlier in the order. • When an order effect is caused by a specific treatment, it is often called a carryover effect. • Progressive error is an order effect which isn’t directly related to a specific treatment, but rather dependent on general experience accumulated during the study. • Common examples of progressive error are practice effects (progressive improvement in performance as a participant gains experience) and fatigue (a progressive decline in performance as participant gains experience). Whenever individuals participate in a series of treatment conditions and experience a series of measurements, their behavior or performance at any point in the series may be influenced by experience that occurred earlier in the sequence. Such influences are called order effects, and include carryover effects and progressive error. Carryover effects are changes in behavior or performance that are caused by participation in an earlier treatment condition. Carryover effects exist whenever one treatment condition produces a change in the participants that affects their scores in subsequent treatment conditions. Progressive error refers to changes in a participant’s behavior or performance that are related to general experience in a research study but not related to a specific treatment or treatments. Common examples of progressive error are practice effects and fatigue. • Order effects, like any confounding variable, can distort the results of a research study. • Order effects can diminish or exaggerate a real effect, thereby posing a real threat to the internal validity of the research. 9.3 Dealing With Time-Related Threats & Order Effects • Experimental factors such as the room, the experimenter, or the time of day, can be controlled by (1) randomization, (2) holding them constant, or (3) matching across treatment conditions. • Controlling time from one treatment condition to the next, a researcher has some control over time-related threats to internal validity. • To note, increasing the time between treatments increases the risk of time-related threats to internal validity. • Outweighing benefits and costs, a researcher must then decide on using within-subjects design method • The process of matching treatments with respect to time is called counterbalancing. • In counterbalancing, different participants undergo the treatment conditions in different orders so that every treatment has some participants who experience the treatment first, some for whom it is second, some third, and so on. • As a result, the treatments are matches or balanced with respect to time. • This procedure disrupts any systematic relationship between time and the order of treatment conditions, and thereby eliminates potential confounding from time-related threats or order effects. Counterbalancing a within-subjects design involves changing the order in which treatment conditions are administered from one participant to another so that the treatment conditions are matched with respect to time. The goal is to use every possible order of treatments with an equal number of individuals participating in each sequence. The purpose of counterbalancing is to eliminate the potential for confounding by disrupting any systematic relationship between the order of treatments and time-related factors. • Counterbalancing requires separate groups of participants with each group going through the series of treatments in a different order. • Although counterbalanc
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