# GLM Repeated Measures Define Factors

GLM Repeated Measures analyzes groups of related dependent variables that represent different measurements of the same attribute. This dialog box lets you define one or more within-subjects factors for use in GLM Repeated Measures. Note that the order in which you specify within-subjects factors is important. Each factor constitutes a level within the previous factor.

To use Repeated Measures, you must set up your data correctly. You must define within-subjects factors in this dialog box. Notice that these factors are not existing variables in your data but rather factors that you define here.

**Example.** In a weight-loss study, suppose the weights of several people are
measured each week for five weeks. In the data file, each person is
a subject or case. The weights for the weeks are recorded in the variables *weight1*, *weight2*, and so on. The gender of each person is recorded in another variable.
The weights, measured for each subject repeatedly, can be grouped
by defining a within-subjects factor. The factor could be called *week*, defined to have five levels. In the
main dialog box, the variables *weight1*, ..., *weight5* are used to assign
the five levels of *week*. The variable
in the data file that groups males and females (*gender*) can be specified as a between-subjects factor
to study the differences between males and females.

**Measures.** If subjects were tested on more than one measure at each time, define
the measures. For example, the pulse and respiration rate could be
measured on each subject every day for a week. These measures do not
exist as variables in the data file but are defined here. A model
with more than one measure is sometimes called a doubly multivariate
repeated measures model.