Guide to using the learning objectives

Learning Objectives for Chapter 14 – Single-n Designs and Quasi-Experiments


Pages 429-443


1.                List1and define1 three criteria you must satisfy in order to infer causality.

2.                Imagine that you want to design a study looking at the effects of surfing the Internet on self-esteem.  Outline3 the role each of the following would play as you design your study:

a.     covariation

b.     temporal precedence

c.     spuriousness.

3.                Compare4 and contrast4 how a simple, two-group, between-subjects experiment and a single-n experiment would deal with covariation, temporal precedence, and spuriousness.

4.                Design5a single-n experiment.

5.                Using the single-n experiment you generated in Objective 4, illustrate3how you could establish a stable baseline.

6.                Describe2the A-B design. Explain2 why it is necessary to establish a stable baseline in A-B design. Describe2 two threats to the validity of an A-B design. 

7.                Describe2each of the following variations on the A-B design:

a.     the reversal design

b.    psychophysical designs

c.     the multiple-baseline design.

8.                Design5each of the following:

a.     the reversal design

b.    a psychophysical design

c.     the multiple-baseline design.

9.                Explain2 why the A-B-A design has more internal validity than the A-B design. Provide3three reasons that behavior in an A-B-A design may not return to baseline after the treatment is withdrawn.

10.           Compare4 and contrast4 single-n designs in terms of (a) internal validity and(b) construct validity.

11.           List1two reasons why people tend to question the external validity of single-n designs. Then, defend4 the statement: “Single-n designs can have external validity.”

12.           Evaluate6 single-n designs on each of the following criteria:

a.     internal validity

b.    construct validity

c.     external validity.

13.           Describe2  two conditions in which single-n designs are most likely to be useful.



Pages 443-460




14.           Define1quasi-experiment. Distinguish4 between quasi-experiments and experiments.

15.           Outline3 the “spurious eight” threats to internal validity. Classify4the spurious eight into three categories: nontreatment factors that cause participants to change, measurement errors that can masquerade as treatment effects, and nontreatment differences between treatment and no-treatment groups.

16.           Describe2 steps you could take to combat each of the eight threats to internal validity.

17.           Describe2 the pretest-posttest design. Contrast4 this design with the A-B single-n design. List1the threats to internal validity that this design eliminates. Explain2 how it eliminates these threats.

18.           Compare4 and contrast4 the time-series design with the pretest-posttest design. Explain2 why the time-series design is less vulnerable to maturation and regression than the pretest-posttest design.

19.           Propose5a study that uses a time-series design.

20.           Illustrate3how the time-series design could estimate the effects of maturation.

21.           Name1the biggest threat to a time-series design’s internal validity. Explain2 why that threat is so serious.

22.           For the time-series study you generated before (in Objective 19), propose5 methods for minimizing each of the following threats to internal validity:

a.     instrumentation

b.    mortality

c.     testing

d.    maturation

e.    history

f.       regression.

23.           Revise4 your time-series study to make it a study that uses a reversal time-series design. Discuss2 the advantages and disadvantages of making this change to your original time-series study.

24.              Revise4 your original time-series study to make it a study that uses a two-group time-series design. Discuss2 the advantages and disadvantages of making this change to your original time-series study.

25.           Outline3 the difference(s) between a simple experiment and a nonequivalent control-group design.

26.           Explain2 why some argue that the no-treatment group in the non-equivalent control-group design should not be called a control group.

27.                Explain2 why matching your groups may not make your treatment and no-treatment groups equivalent. Be sure to include the terms selection by maturation interaction and regression in your answer.

28.                Define1law of parsimony. Explain2 how quasi-experimenters use this law.


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