Non-Experimental Approaches to Research

Nuances

You need to establish a stable baseline before the treatment is introduced.

An interrupted time series is sometimes defined as having a treatment which is a natural event as compared to one introduced by the experimenter.

 

Here's an example from a study analyzing the effect of a new gun law on crime. Note the base rate for several years before the law took effect and the decrease in crime after its passage.

3. Multiple Time Series

This design is used to attempt to rule out possible alternative interpretations. Maybe in Lott and Mustard's study, some other event decreased crime. You might then compare their location against an area that did not pass the same law. The results might look like the smaller graph above. The control group doesn't show the change across time.


Single Subject Designs

1. Advantages and Disadvantages

Observation of a single subject has a noble tradition in Psychology. Some of our most basic principles in areas of Perception and memory were discovered using it. It is still an incredibly useful technique in these fields. It is also a mainstay of research in Clinical Psychology where one focuses on the progress of a client.

One major advantage is the focus on individual performance. A classic example is in the field of learning. If you plotted correct performance on a memory task for a group of subjects, one might conclude that learning is a gradual process. Or is it because a grouped graph sums over a number of subjects learning the item in an all or none fashion but over different trials. Look for this conundrum in the graphic below. Another advantage related to clinical work is that you don't leave individuals untreated in control groups. Single subject designs also allow flexibility in design. If a treatment is not working - it is easy to change.

What are some of the disadvantages? :

Some effects are small and can't really be seen in one subject.

Sometimes you can't try out different variables on the same subject and you must use between-subject designs.

2. Techniques commonly used are:

Time Series

Interrupted Time Series

Multiple Time Series

Useful techniques of testing include:

Withdrawal of Treatment Designs (ABA - baseline, treatment, withdraw treatment)

ABAB - as above but with treatment resumed after withdrawal

Interaction Designs A-B-A-B--BC-B-BC. The purpose is to see if C has an effect in addition to B.