By definition, all experiments involve manipulation of one or more independent variables, and observing the effect on some outcome (dependent variable). Experiments can be done in the field or in a laboratory. They can involve human or animal subjects. What distinguishes the type of experiment is the degree to which the experimenter can assign subjects to conditions. Three types are described here: True, Quasi- and Single-subject experiments.
| True experiments
In a true experiment, subjects are randomly assigned to the treatment conditions (levels of the independent variable). The only differences in the groups would be due to chance. True experiments are excellent for showing a cause-and-effect relationship. Random assignment (or random assignment within matched groups) controls for extraneous variables. They tend to be high on internal validity. It is clear what is being measured. There still might be bias in the overall research design, but at least variables associated with individuals are not a source of constant error (see sources of error in the Sampling module). |
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Quasi-experiments
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One type of quasi experiment is to compare treatment versus control conditions, where the assignment has occurred as a result of some natural event. For example, comparing tranquilizer sales in a community struck by a hurricane, with sales in a similar community that was not affected by the hurricane. Or to compare drinking levels at two colleges with similar student bodies, one with an orientation programs with respect to alcohol use, and the other having no such program. More....
Another type of quasi-experiment is to compare pre- versus post- events or behavior, for example
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Single-subject experiments
Instead of comparing behavior or performance of groups of people at a single point in time, a single-subject experiment involves a single case studied over a longer period of time. One individual or situation is exposed to the varying levels of the independent variable.
constant
error - error resulting from bias; or from improper sampling
or bad design |
internal
validity - degree to which a procedure measures what
it is supposed to measure. |
reliability -
consistency in measurement; the repeatability or replicability of findings, stability
of measurement over time.
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The most simple single-subject research design is termed ABA, where A is the baseline (non-treatment or control) condition or phase. B refers to the introduction of the treatment factor. Behavior is recorded in both stages. Then there is a return to A to see if in fact it was B that brought about the change. An example might be treating a hyperactive child with a drug. Stage A involves recording the child's behavior before any treatment, e.g., how many disruptive events in the classroom within a specified period of time. Stage B would involve the same measurement after the child has been treated. If B (the treatment) makes a difference, returning to level A (no treatment) should result in a return of the disruptive behavior. The basic research design can include a second treatment phase -- ABAB, thereby increasing the reliability and internal validity of the results.
The subject of a single-subject experiment might be an entire community. For example, police in a small city introduced helicopter patrols to see whether or not they resulted in a decrease in burglaries. Here is a figure showing the results.
This is an ABABA design.
The occurrence of burglaries tended to be higher when the helicopter was not on patrol. In setting policy the officials would have to weigh the benefit against the added cost.
true vs. quasi- and lab vs. field studies
It is easy to confuse setting with experiment type. Use the table below to keep them straight.
TYPE LOCATION True Quasi- (natural) Lab
common unusual less common common Field Although quasi-experiments are not commonly done in a lab, some of the subject variables in lab-run experiments, such as gender or socioeconomic level, are not subject to random assignment.
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