Chapter 13: Quasi-experiments and small-N Designs Flashcards
Quasi-experiments
A study similar to an experiment except that the researchers do not have full experimental control (e.g., they may not be able to randomly assign participants to IV conditions).
Quasi-independent variable
A variable that resembles an IV, but the researcher does not have truth control over it (e.g., cannot randomly assign participants to its levels or cannot control its timing).
Nonequivalent control group design
A quasi-experiment that has at least one treatment group and one comparison group, but participants have not been randomly assigned to the two groups.
Nonequivalent control group posttest-only design
A quasi-experiment where participants were not randomly assigned to groups and were only tested once, after exposure to one level of the IV or the other.
Nonequivalent control group pretest/posttest design
A quasi-experiment that has at least one treatment group and one comparison group, in which participants have not been randomly assigned to the two groups, and in which at least one pretest and one posttest are administered.
Interrupted time-series design
A quasi-experiment in which participants are measured repeatedly on a DV before, during, and after the “interruption” caused by some event.
Nonequivalent control group interrupted time-series design
A quasi-experiment with two or more groups in which participants have not been randomly assigned to groups; participants are measured repeatedly on a DV before, during, and after the “interruption” caused by some event, and the presence or timing of the interrupting event differs among the groups.
Wait-list design
An experimental design for studying a therapeutic treatment, in which researchers randomly assigned some participants to receive the therapy under investigation immediately, and others to receive it after a time delay.
Internal validity threats in quasi experiments
- Selection effects
- Design confounds
- Maturation threat
- History threat
- Selection-history threat
- Regression to the mean
- Attrition threat
- Testing threat
- Instrumentation threat
Selection effects
Participants vary systematically between levels of an IV. Only applies to independent-groups designs.
Control for this using pretest/posttest design, matched-groups, or wait-list design.
Design confounds
Some outside variable accidentally and systematically varies with the levels of the targeted IV.
Maturation threat
An observed change emerges more or less spontaneously over time, not due to effect of IV.
History threat
An external, historical event happens for everyone in the study at the same time as the treatment.
Selection-history threat
The historical event systematically affects participants only in the treatment group or only in the comparison group, not both.
Regression to the mean
An extreme outcome is caused by a combination of random factors that are unlikely to happen in the same combination again.
Attrition threat
When systematic kinds of people drop out of the study.
Testing threat
A kind of order effect in which participants tend to change as a result of having been tested before.
Instrumentation threat
A measuring instrument (observer or self-report) changes over time.
Observer bias
The experimenters expectations influence their interpretation of the results.
Interrogate by asking who measured the behaviors.
Demand characteristics
Participant guess what the study is about and change their behavior in the expected direction.
Interrogate by considering whether the participants were able to detect the study’s goals and respond accordingly.
Placebo effects
Participants improve, but only because they believe they are receiving an effective treatment.
Interrogate by asking whether the design included a comparison group that received an inert/placebo treatment.
Stable-baseline design
A study in which a practitioner a researcher observes behavior for an extended baseline before beginning of treatment or other intervention.
Multiple baseline-design
Researchers stagger their introduction of an intervention across a variety of individuals, times, or situations to rule out alternative explanations.
Reversal design
A small-N design in which a researcher observes a problem behavior both before and during treatment, and then discontinues the treatment for a while to see if the problem behavior returns. They subsequently re-introduce the treatment to see if the behavior improves again.
