Between Vs. Within Subjects Designs Essay

1359 words - 5 pages

In simplest terms, an experiment that uses only between-subjects factors is said to use a between-subjects design, and an experiment that uses only within-subjects factors is called a within-subjects design. The fundamental hallmark of a between-subjects design is that each participant is assigned to one and only one level of each factor. For instance, participants might be randomly assigned to either receive negative feedback or positive feedback. Feedback is the independent variable, and it has two levels: positive or negative. It is a between-subjects design because each participant only receives one type of feedback. There are two (2) independent groups of participants in the study: one group receives positive feedback and the other group receives negative feedback (Charness, Gneezy, & Kuhn, 2012). In a between-subjects design, the typical approach to statistical analysis is to compare the means of the different levels of the between-subjects factors. Using the above explanation, an experimenter might measure each participant’s self esteem, for example, after he/she has received feedback. The mean self-esteem score for the positive feedback group would than be compared to the mean self-esteem score for the negative feedback group (Thompson & Campbell, 2004). The experimenter’s goal, in this example, would be to explain as much of the variance as possible between the two means: positive and negative. The variance that can be explained is the variance due to being in the positive versus the negative feedback condition. The variance can be explained because you have an independent variable; in this experiment, it would be the feedback condition. However, the experimenter could not explain why one participant in the condition has a self-esteem score of 42 and another participant has a score of 48. The experimenter couldn’t explain this difference because they do not have any variables that distinguish those two participants; the experimenter doesn’t have any information about how they may differ from one another. This is referred to as “error variance” (Erlebacher, 1977). Error variance is the differences between scores that an experimenter cannot explain. In a between-subjects design, error variance is the variability in the scores within each condition. As the scores within each condition become more spread out, error variance increases. As the error variance increases, it becomes harder to detect whether an effect exists; for example, whether the type of feedback influences self-esteem. An inherent consequence of this is that experimenters do what they can to reduce within-condition variability. They are able to do this by: 1) treating every participant within a condition as similarly as possible; and 2) by seeking a homogeneous sample which is a sample of individuals who are very similar to one another. This accomplishes the following: it reduces error variance and the experimenter is better able to get a diverse...

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