Chapter 10
Quasi-Experimental and Single-Case Designs

 

(Reminder: Don’t forget to utilize the concept maps and study questions as you study this and the other chapters.)


The experimental research designs discussed in this chapter are used when it is impossible to randomly assign participants to comparison groups (quasi-experimental designs) and when a researcher is faced with a situation where only one or two participants can participate in the research study (single case designs).

 

 

Quasi-Experimental Research Designs

These are designs that are used when it is not possible to control for all potentially confounding variables; in most cases this is because the participants cannot be randomly assigned to the groups.

 

 

                /------------------------------------/------------------------------------/

Weak                                       Quasi                                       Strong

Designs                                    Designs                                    Designs

 

 

 

 

Nonequivalent Comparison-Group Design

This is a design that contains a treatment group and a nonequivalent untreated comparison group about of which are administered pretest and posttest measures. The groups are “nonequivalent” because you lack random assignment (although there are some control techniques that can help make the groups similar such as matching and statistical control). Because of the lack of random assignment, there is no assurance that the groups are highly are similar at the outset of the study.
 

Here is a depiction of the nonequivalent comparison-group design:

 

 

 

 

 

 

Interrupted Time-Series Design

This is a design in which a treatment condition is accessed by comparing the pattern of pretest responses with the pattern of posttest responses obtained from a single group of participants. In other words, the participants are pretested a number of times and then posttested a number of times after or during exposure to the treatment condition.

 

Here is a depiction of the interrupted time-series design:

 

 

 

 

 

·        Many confounding variables are ruled out in the interrupted time-series design because they are present in both the pretreatment and posttreatment responses (i.e., the pretreatment and posttreatment responses will not differ on most confounding variables).

 

·        However, the main potentially confounding variable that cannot be ruled out is a history effect. The history threat is a plausible rival explanation if some event other than the treatment co-occurs with the onset of the treatment.
 

Bonus material (not required)

Although not discussed in the text, there is an extension of the interrupted time-series design. It is called the multiple time-series design—it is the basic interrupted time-series design with a comparable control group added to it. I mention this design because I do want you to remember that YOU can put together different designs simply by using different combinations of pretests, posttests, different types of groups, varying the number of pretests and posttests, using a control group or not, including more than one outcome variable, and so forth.

 

 

 

 

Regression Discontinuity Design

This is a design that is used to access the effect of a treatment condition by looking for a discontinuity in regression lines between individuals who score lower and higher than some predetermined cutoff score on an assignment variable. 

 

 

 

 

Here is an example where a difference or “discontinuity” is easily seen:

 

 

 

 

 

Single-Case Experimental Designs

These are designs where the researcher attempts to demonstrate an experimental treatment effect using single participants, one at a time.

 

A-B-A and A-B-A-B Designs

The A-B-A design is a design in which the participant is repeatedly pretested (the first A phase or baseline condition), then the experimental treatment condition is administered and the participant is repeatedly posttested (the B phase or treatment phase).  Following the posttesting stage, the pretreatment conditions are reinstated and the participant is again repeatedly tested on the dependent variable (the second A phase or the return to baseline condition).

 

 

 

 

 

 

Multiple-Baseline Design

This is a design that investigates two or more people, behaviors, or settings to identify the effect of an experimental treatment. The key is that the treatment condition is successively administered to the different people, behaviors, or settings.

·        Here is a depiction of the design:

 

 

 

·        The multiple-baseline design requires that baseline behavior is collected on the several people, behaviors, or settings and then the experimental treatment is successively administered to the people, behaviors, or settings.

·        The experimental treatment effect is demonstrated if a change in response occurs when the treatment is administered to each person, behavior, or setting (i.e., when the fingerprint you are looking for is observed).

 

·        Here is an example where a treatment fingerprint is easily seen:

 

 

 

Changing-Criterion Design

This is a single-case design that is used when a behavior needs to be shaped over time or when it is necessary to gradually change a behavior through successive treatment periods to reach a desired criterion.

 

 

Methodological Considerations in
Using Single-Case Designs

The following table presents some major methodological issues you must consider when using single-case designs.