Using Linear Mixed Models to Analyze a Crossover Trial
A grocery store chain is interested in determining the effects of three different coupons (versus no coupon) on customer spending. To this end, they construct a crossover trial in which a random sample of their regular customers is followed for four weeks. Since they are concerned about carryover effects, the sequence of coupons sent to each customer is carefully considered, and the following table is used:
| Week | Sequence 1 | Sequence 2 | Sequence 3 | Sequence 4 |
|---|---|---|---|---|
| Week 1 | No coupon | 5 percent | 15 percent | 25 percent |
| Week 2 | 5 percent | 25 percent | No coupon | 15 percent |
| Week 3 | 15 percent | No coupon | 25 percent | 5 percent |
| Week 4 | 25 percent | 15 percent | 5 percent | No coupon |
Thus, in Sequence 1, a customer is not sent a coupon in the first week, receives a 5 percent coupon in the second week, a 15 percent coupon in the third week, and a 25 percent coupon in the fourth week. Each customer is randomly assigned to one of the sequences.
This information is collected in grocery_coupons.sav. See the topic Sample Files for more information. Use the Linear Mixed Models procedure to analyze the crossover trial.