Ch. 8 Flashcards
one-group posttest only design
A treatment is implemented (or an independent variable is manipulated) and then a dependent variable is measured once after the treatment is implemented.
weakest type of quasi-experimental design.
A major limitation to this design is the lack of a control or comparison group.
Despite this major limitation, results from this design are frequently reported in the media and are often misinterpreted by the general population.
If there is no comparison group, then this statistic means little to nothing.
one-group pretest-posttest design
An experiment design in which the dependent variable is measured once before the treatment is implemented and once after it is implemented.
is much like a within-subjects experiment in which each participant is tested first under the control condition and then under the treatment condition.
It is unlike a within-subjects experiment, however, in that the order of conditions is not counterbalanced because it typically is not possible for a participant to be tested in the treatment condition first and then in an “untreated” control condition.
Unfortunately, one often cannot conclude this with a high degree of certainty because there may be other explanations for why the posttest scores may have changed.
These alternative explanations pose threats to internal validity.
alternative explanations to post test and pretest
history
Events outside of the pretest-posttest research design that might have influenced many or all of the participants between the pretest and the posttest.
alternative explanations to post test and pretest
maturation
Participants might have changed between the pretest and the posttest in ways that they were going to anyway because they are growing and learning.
alternative explanations to post test and pretest
testing
A threat to internal validity that occurs when the measurement of the dependent variable during the pretest affects participants’ responses at posttest.
alternative explanations to post test and pretest
instrumentation
A potential threat to internal validity when the basic characteristics of the measuring instrument change over the course of the study.
When human observers are used to measure behavior, they may over time gain skill, become fatigued, or change the standards on which observations are based.
alternative explanations to post test and pretest
regression to the mean
Refers to the statistical fact that an individual who scores extremely high or extremely low on a variable on one occasion will tend to score less extremely on the next occasion.
Regression to the mean can be a problem when participants are selected for further study because of their extreme scores.
alternative explanations to post test and pretest
spontaneous remission
The tendency for many medical and psychological problems to improve over time without any form of treatment.
The common cold is a good example.
If one were to measure symptom severity in 100 common cold sufferers today, give them a bowl of chicken soup every day, and then measure their symptom severity again in a week, they would probably be much improved.
This does not mean that the chicken soup was responsible for the improvement, however, because they would have been much improved without any treatment at all.
Thus one must generally be very cautious about inferring causality from pretest-posttest designs.
A common approach to ruling out the threats to internal validity
is by revisiting the research design to include a control group, one that does not receive the treatment effect.
A control group would be subject to the same threats from history, maturation, testing, instrumentation, regression to the mean, and spontaneous remission and so would allow the researcher to measure the actual effect of the treatment (if any).
Of course, including a control group would mean that this is no longer a one-group design.
Interrupted Time Series Design
A set of measurements taken at intervals over a period of time that is “interrupted” by a treatment.
the interrupted time-series design is like a pretest-posttest design in that it includes measurements of the dependent variable both before and after the treatment.
It is unlike the pretest-posttest design, however, in that it includes multiple pretest and posttest measurements.
nonequivalent groups design
A between-subjects design in which participants have not been randomly assigned to conditions.
When participants are not randomly assigned to conditions, however, the resulting groups are likely to be dissimilar in some ways. For this reason, researchers consider them to be nonequivalent.
posttest only nonequivalent groups design
Participants in one group are exposed to a treatment, a nonequivalent group is not exposed to the treatment, and then the two groups are compared.
researchers using a posttest only nonequivalent groups design can take steps to ensure that their groups are as similar as possible.
But without true random assignment of the students to conditions, there remains the possibility of other important confounding variables that the researcher was not able to control.
pretest-posttest nonequivalent groups design
In this design there is a treatment group that is given a pretest, receives a treatment, and then is given a posttest.
Then, at the same time there is a nonequivalent control group that is given a pretest, does not receive the treatment, and then is given a posttest.
The question, then, is not simply whether participants who receive the treatment improve, but whether they improve more than participants who do not receive the treatment.
This type of design does not completely eliminate the possibility of confounding variables, however.
interrupted time-series design with nonequivalent groups
Involves taking a set of measurements at intervals over a period of time both before and after an intervention of interest in two or more nonequivalent groups.
pretest-posttest design with switching replication design
In this design nonequivalent groups are administered a pretest of the dependent variable, then one group receives a treatment while a nonequivalent control group does not receive a treatment, the dependent variable is assessed again, and then the treatment is added to the control group, and finally the dependent variable is assessed one last time.
One of the strengths of this design is that it includes a built in replication.
Another strength of this design is that it provides more control over history effects.
It becomes rather unlikely that some outside event would perfectly coincide with the introduction of the treatment in the first group and with the delayed introduction of the treatment in the second group.
Similarly, the switching replication helps to control for maturation and instrumentation.
Of course, demand characteristics, placebo effects, and experimenter expectancy effects can still be problems.
switching replication with treatment removal design
In this design the treatment is removed from the first group when it is added to the second group.
Demonstrating a treatment effect in two groups staggered over time and demonstrating the reversal of the treatment effect after the treatment has been removed can provide strong evidence for the efficacy of the treatment.
In addition to providing evidence for the replicability of the findings, this design can also provide evidence for whether the treatment continues to show effects after it has been withdrawn.
