Discussion
wk14
factorial designs, repeated measure designs, and mixed design. Explain in your own words
the difference between these. Give specific examples for which you would choose one
method instead of the others.
According to Andy Field1, the word “factors” are sometimes used to refer to independent
variables; therefore, a factorial design refer to an experiment involving two or more independent
variables. There are different types of factorial designs, including: independent factorial design,
repeated-measure design factorial design, and mixed factorial design. An independent factorial
design involves several independent variables measured using different entities. A repeated-
measure design involves independent variables measured using the same entities across all
conditions. A mixed measure design involves some independent variables measured using the
same and some using different entities.
If you want to test mathematical skills in gender differences you can only use independent
factorial design, because gender involves two discrete values (female or male). You cannot force
a female to become male later and then test her again. If we want to test the effects of a
pharmacological treatment on a very rare disease, you should use repeated-measure designs.
Firstly, it is difficult to find a large number of feasible patients who have the same very rare
disease. Secondly, you want to see the effects of the treatment over time with all other factors
being the same (testing the same patient is the best way to ensure other physiological
comorbidities are the same). Repeated-measure designs are usually used in longitudinal studies.
Mixed design is needed when you need to combine both repeated-measure and independent
design in an experiment. For example, you want to test mathematical skills before and after a
math class in gender differences. Mathematical skills before and after a math class will be the
repeated measures, and gender will be the independent measure. Again, you cannot force a
female to become male later and then test her again, and it doesn’t make sense to compare a
student’s mathematical skills before a class to another student’s mathematical skills after a class.
Reference:
1. Andy Field. Discovering Statistics Using IBM SPSS Statistics: North American Edition.
5th ed. London: SAGE Publications, Inc. 2018.
