In: Statistics and Probability
When a study has at least one between-subjects factor and at least one within-subjects factor, it is said to have a “mixed” design.
An Example:
To compare three teaching methods, an experiment was conducted in which one group was taught probability by a Traditional method (T1), a second group was given additional problems (T2), and a third group received further problems from a computer that provided immediate feedback (T3). We expect that the new teaching method (T3) will be more effective than the traditional teaching method ( T1). However, people might ask the question about how long the comparative advantage of the new teaching method will last. It might be possible that at the beginning the new teaching method is better than the traditional one. But as time pass by, the new teaching method may lose its comparative advantage. Therefore, the effects of the three teaching methods are compared on multiple occasions. Here, all three groups were tested at the end of the instructional period, and then once every 2 weeks until four different tests had been given. The following table presents a data set for this hypothetical experiment. Assume that the tests were equated for difficulty so that any differences could be attributed to the passage of time. This design permits us to compare the instructional methods (A) and also to see the time course (B) following the end of instruction for each method.