This long awaited successor of the original Cook/Campbell Quasi-Experimentation: Design and Analysis Issues
for Field Settings represents updates in the field over the last two decades.This edition places a new emphasis
on the generalization of causal connections and design elements rather than designs, with extensive attention given
to methods for studying external validity. The authors pay specific attention to describing how testing casual
propositions can be improved in specific research projects and outline ways to improve generalizations about them
through field experimentation.
Instead of focusing on the statistical analysis of data, the text considers these details in brief paragraphs or
chapter appendices, using a conceptual focus and leaving most equations in footnotes. In addition, three chapters
are devoted to the logic and design of randomized experiments, and the practical problems and solutions in their
implementation.
Key terms are bolded within the text and defined in a glossary.
The text presents minor changes to Campbell's general conceptual scheme--validity typology.
Table of Contents
1. Experiments and Generalized Causal Inference
2. Statistical Conclusion Validity and Internal Validity
3. Construct Validity and External Validity
4. Quasi-Experimental Designs That Either Lack a Control Group or Lack Pretest Observations on the Outcome
5. Quasi-Experimentation: Designs That Use Both Control Groups and Pretests
6. Quasi-Experimentation: Interrupted Time Series Designs
7. Regression Discontinuity Designs
8. Randomized Experiments: Rationale, Designs, and Conditions Conducive to Doing Them
9. Practical Problems I: Ethics, Participant Recruitment, and Random Assignment
10. Practical Problems II: Treatment Implementation and Attrition
11. Generalized Causal Generalization: A Grounded Theory
12. Generalized Causal Generalization: Methods for Single Studies
13. Generalized Causal Generalization: Methods for Multiple Studies
14. A Critical Assessment of Our Assumptions
