Answer to Question 1
A within-subjects design involves repeated measures because with each treatment the same subject is measured. In contrast, a between-subjects design measure each dependent variable only once for each subject. Between-subjects designs are usually advantageous although they are usually more costly. The validity of between-subjects designs is usually higher because by applying only one treatment combination to one subject, demand characteristics are greatly reduced. When a subject sees multiple conditions, he or she is more likely to guess what the study is about. In addition, statistical analyses of between-subjects designs are simpler than within-subjects designs. This also means the results are easier to report and explain to management.
Answer to Question 2
The term demand characteristic refers to an experimental design element that unintentionally provides subjects with hints about the research hypothesis. Knowledge of the experimental hypothesis creates a confound known as a demand effect. Demand characteristics are aspects of an experiment that demand (encourage) that the subjects respond in a particular way, hence being a source of systematic error. Ways of reducing demand characteristics include the following:
(1) Use an experimental disguise.
(2) Isolate experimental subjects.
(3) Use a blind experimental administrator.
(4) Administer only one experimental treatment level to each subject.
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