Independent, Dependent, and Subject Variables

In experimental research, there is always at least one variable actively changed or manipulated by the experimenter. Generally it is the suspected cause in a cause-effect relationship. This is the independent variable. To remember this term, think of the independent variable as the one that can be manipulated independently (by itself) while changes are observed in a host of other variables. Or think of the an experimenter as an agent of change, an independent force that can manipulate this variable to see what happens in different situations.

What are independent and dependent variables? Can there be more than one dependent variable?

What are subject variables?

Variables measured to see possible effects of a manipulation are dependent variables. The values of this variable might depend upon the manipulation of the independent variables. The experiment is designed to find this out. Using the language of cause and effect, the dependent variable is suspected of being an effect. There can be many dependent variables examined by an experimenter—many possible effects of a manipulation.

Subject variables are a third category of variables commonly found in psychology research. The subject's age, sex, height, and weight are subject variables. They are not manipulated as part of the research (thus they are not independent variables) and they are not measured to see changes after a manipulation (thus they are not dependent variables). They are characteristics of the subject. A researcher keeps track of them to see if they bear any relationship to the results (for example, to see if the effects of a treatment vary with the age of the subject).

How does a two-group comparison work? What is an experimental group? A control group?

A common type of experiment used to gather evidence about cause-effect claims is the two-group comparison. One group, the experimental group , receives a treatment designed to produce some effect(a manipulation of the independent variable). The other group, the control group , is left alone or given a fake treatment. Data is gathered; the dependent variables are measured. Results from the two groups are compared and analyzed to see if the experimental treatment made any difference.

What is the difference between a between-subjects and within-subject design?

This type of experiment is called a between-subjects design The comparison is between two or more different groups of subjects. By contrast, a within-subject design compares changes within the same subject on different occasions. In a within-subjects design, each subject serves as his or her own control or standard of comparison. An example of a within-subject design is a "before and after" comparison. For example, we might compare a person's eyesight using several different types of glasses, using 50 subjects, to determine which glasses work best for the most people. Within-subjects designs are subject to practice effects (described on p.33). A person being tested on an eye chart might remember some answers from the earlier test. Unless the effects of practice are the focus of research, one must remain alert for practice effects whenever the same subjects are tested twice using the same sort of test.


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