Research Design Notation

Post date: Aug 26, 2012 4:39:0 PM

This notation is mostly used in the context of studies in which interventions (treatments) are performed on some groups of subjects. For simplicity, we deal only with the case of two or more groups.

Design 1. Post-test only randomized experiment

Each row is a group. The R indicates a randomized assignment of each subject to the group. The X indicates an intervention or treatment of some kind (such as being given a drug). The O indicates measurement of the dependent variable. So in this example, the subjects are randomly assigned to one of two groups. One of these groups gets the treatment, and the other does not. Then, after a certain amount of time, an outcome is measured for each person in all groups.

Design 2. Pre-Post randomized experiment

If the group sizes are small, randomized assignment doesn't guarantee that the resulting groups are really the same. In that case it would be better to measure the dependent variable before the treatment as well. Of course, this may introduce its own problems, as it may give away what the dependent variable is.

Design 3. Pre-Post non-randomized quasi experiment

The N indicates a non-random assignment to a group. As you can see, a baseline measurement is made of the dependent variable in both groups, and then an intervention is applied to one group. Then the dependent variable is measured again. We refer to this as a quasi-experiment (or natural experiment) because of the lack of randomized assignment to groups. An example is when

Design 4. Post-only non-randomized non-experiment

If the difference between the two groups is defined by X, this is your basic correlational study, whether X was an intervention or not. For example, many medical studies will compare cancer rates for, say, smokers and non-smokers, and show that smokers are more likely to be get cancer. Obviously, they will try control for other differences between the smokers and non-smokers, but they likely differ in hundreds or thousands of ways, so there is no way to control for all of these things.

Design 5. Post-test only non-experiment

Here there is just one group, and everyone receives the treatment. Then an outcome is measured. This is largely useless. Note that it doesn't matter whether X is a deliberate intervention, such as a training class, or something that happened and is studied after the fact. For example, we might study soldiers returning from active duty (X) to see if they have psychological problems (O).