CH. 13 Quasi-Experiments and Small-N Designs

Question 1

What is a quasi-experiment?

Answer 1

Researchers do not have full experimental control.
(In a quasi-experiment, the researchers might not be able to randomly assign participants to one level or the other; they are assigned by teachers, political regulations, acts of nature—or even by their own choice.)

Question 2

What is a nonequivalent control group design?

Answer 2

It has at least one treatment group and one comparison group, but unlike in a true experiment, participants have not been randomly assigned to the two groups.
see p. 390 in text for example

Question 3

What is a nonequivalent control group pretest/ posttest design?

Answer 3

Participants are not randomly assigned to groups, and were tested both before and after some intervention.

Question 4

What is an interrupted time-series design?

Answer 4

A quasi-experimental study that measures participants repeatedly on a dependent variable before, during, and after the “interruption” caused by some event.
see p. 394 in text for example

Question 5

What is a nonequivalent control group interrupted time-series design?

Answer 5

It combines two of the previous designs (the nonequivalent control group design and the interrupted time- series design). In this example, the independent variable was studied as both a repeated-measures variable (interrupted time-series) and an independent-groups variable (nonequivalent control group). In both cases, however, the researchers did not have experimental control over either independent variable.
see p. 396

Question 6

How might researchers control for selection effects in an independent groups quasi experimental design?

Answer 6

By using a wait-list design, in which all the participants plan to receive treatment but are randomly assigned to do so at different times.

Question 7

What is a design confound?

Answer 7

Some outside variable accidentally and systematically varies with the levels of the targeted independent variable

Question 8

What is a maturation threat?

Answer 8

Maturation threats occur when, in an experimental or quasi-experimental design with a pretest and posttest, an observed change could have emerged more or less spontaneously over time.

Question 9

What is a history threat?

Answer 9

A history threat occurs when an external, historical event happens for everyone in a study at the same time as the treatment. With a history threat, it is unclear whether the outcome is caused by the treatment or by the external event or factor.

Question 10

What is regression to the mean?

Answer 10

Regression to the mean occurs when an extreme finding is caused by a combination of random factors that are unlikely to happen in the same combination again, so the extreme finding gets less extreme over time.

Question 11

What is attrition threat?

Answer 11

In designs with pretests and posttests, attrition occurs when people drop out of a study over time. Attrition becomes an internal validity threat when systematic kinds of people drop out of a study.

Question 12

Testing threat?

Answer 12

A testing threat is a kind of order effect in which participants tend to change as a result of having been tested before. Repeated testing might cause people to improve, regardless of the treatment they received. Repeated testing might also cause performance to d

Question 13

Instrumentation threat?

Answer 13

Instrumentation, too, can be an internal validity threat when participants are tested or observed twice. A measuring instrument could change over repeated uses, and this change would threaten internal validity. If a study uses two versions of a test with different standards (e.g., one test is more difficult) or if a study uses coders who change their standards over time, then participants might appear to change, when in reality there is no change between one observation and the next.

Question 14

What do researchers give up when they conduct studies in which they don’t have full experimental control?

Answer 14

The main concern is internal validity—the ability to draw causal conclusions from the results. The degree to which a quasi-experiment supports a causal claim depends on two things: its design and its results. Threats to internal validity include: selection effects, maturation, attrition ect.

Question 15

Why might researchers choose to conduct a quasi-experimental design?

Answer 15

1. Present real-world opportunities for studying interesting phenomena and important events
2. The real-world settings of many quasi-experiments can enhance external validity because of the likelihood that the patterns observed will generalize to other
   circumstances and other individuals.
3. Many questions of interest to researchers would be unethical to study in a true experiment

Question 16

What is a small-N design (specifically, what does “N” refer to)?

Answer 16

N refers to sample size
In a small-N design, researchers collect a lot of information from just a few cases, rather than a little information from a large sample.

Question 17

What are some advantages of case study research?

Answer 17

• empirical strength of studies means we can draw conclusions from them
• small-N studies often take advantage of special medical cases (ex. H.M)

Question 18

What is a disadvantage to small-N studies?

Answer 18

-external validity: participants in small-N studies may not represent general population very well

Question 19

Describe: stable-baseline design

Answer 19

A study in which a practitioner or researcher observes behavior for an extended baseline period before beginning a treatment or other intervention. If behavior during the baseline is stable, the researcher is more certain of the treatment’s effectiveness.

Question 20

Describe: multiple-baseline designs

Answer 20

In a multiple-baseline design, researchers stagger their introduction of an intervention across a variety of individuals, times, or situations to rule out alternative explanations.

Question 21

Describe: reversal design.

Answer 21

In a reversal design, as in the other two small-N designs (stable baseline and multiple baseline), a researcher observes a problem behavior both with and without treatment, but takes the treatment away for a while (the reversal period) to see whether the problem behavior returns (reverses). They subsequently reintroduce the treatment to see if the behavior improves again.