Types of Experiments & Research Designs. UAPP 702: Research Design for Urban & Public Policy Based on notes from Steven W. Peuquet. Ph.D. Types of Experiments. There are four kinds of experiments: True experiments Quasi-experiments Natural experiments Naturalistic experiments.
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UAPP 702: Research Design for Urban & Public Policy
Based on notes from Steven W. Peuquet. Ph.D.
There are four kinds of experiments:
1. Need at least two groups: anexperimental group and a control group. One groups gets the intervention, the other group does not.
2. Random assignment of individuals to the groups. (The degree to which random assignment ensures equivalence of the groups is dependant upon the size of the groups.)
3. The groups are measured on one or more dependent variables. This is called the pretest.
4. The intervention (independent variable) is introduced.
5. The dependent variables are measured again. This is the post test.
In a study of the effectiveness of a new math curriculum, a 6th grade class in Porter Middle School was not given the new curriculum (the “control group”), while the 6th grade class in Farley Middle School was given the new curriculum (experimental group).
At the end of the school year the 6th graders in the Farley MS class had higher average math achievement test scores than the kids in the Porter MS 6th grade class.
Is this a “quasi-experiment”? Why?
Answer: Most likely -- YES
Random assignment to the two classes was probably not made, hence, groups may not be equivalent. Possibility of results being confounded by socio-economic status (SES) or other factors.
Natural experiments are happening around us all the time. They are not conducted by researchers, but simply evaluated by researchers. In other words, the researcher does not have control over the application of the treatment. This also means that there is no control over what groups receive the treatment and the composition of those groups.
Note: Each of these situations tests something
about human behavior, the question is: “What
is being tested by what is going on?”
In naturalistic experiments, one contrives to collect experimental data under natural conditions. You make the data happen out in the natural world (not in the lab), and you evaluate the results.
The difference between a natural experiment and a naturalistic experiment is that the first just happens, the second must be contrived to happen.
Naturalistic experiments deviate from true experiments because group membership is not randomly assigned, and exogenous factors (confounding variables) are not controlled.
Internal validity can be increased by:
Controlled experiments have the virtue of producing results with high internal validity, but they have the liability of low external validity
External validity is the extent to which the cause and effect relationship can be generalized to other groups that were not part of the experiment.
External validity is critically important in policy and program evaluation research because we would like our research findings to be generalizable. If external validity is low, then the results are not generalizable.
History confound —
Any independent variable other than the treatment variable, that occurs between the pre-test and the post-test.
Maturation confound —
Refers to the fact that as the experiment is conducted, people are growing older, and are getting more experienced. (Problem in longitudinal studies in particular)
Testing confound —
Refers to different responses that an experimental subject may have to questions they are asked over and over again.
Instrumentation confound —
Results from changing measurement instruments. (Example: use of different people to collect data, if there is no inter-rate reliability, you have changed the measurement instrument.)
Regression to the mean —
Groups tend to increasingly resemble the mean over time.
Selection bias confound —
When self-selection by individuals into groups is possible, a selection bias can result.
Diffusion of treatment
Occurs when a control group cannot be prevented from receiving the treatment in an experiment.
Let’s look at two related but different research questions, and see what types of experiments would be appropriate for each.
NEVER USE A RESEARCH DESIGN OF LESS LOGICAL POWER WHEN ONE OF GREATER LOGICAL POWER IS FEASIBLE !