Synopses & Reviews
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. The book covers four major topics in field experimentation: Theoretical matters: Experimentation, causation, and validityQuasi-experimental design: Regression discontinuity designs, interrupted time series designs, quasi-experimental designs that use both pretests and control groups, and other designsRandomized experiments: Logic and design issues, and practical problems involving ethics, recruitment, assignment, treatment implementation, and attritionGeneralized causal inference: A grounded theory of generalized causal inference, along with methods for implementing that theory in single and multiple studies
"...I received my book yesterday...thank you so much! I used the 1979 version a lot in my PhD program and am eagerly re-reading it. It's a great experimental design book and is excellent for explaining validity issues to students!"
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. The book covers four major topics in field experimentation:
Includes bibliographical references (p. 514-591) and indexes.
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-Experimental 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 1: Ethics, Participant Recruitment, and Random Assignment 10. Practical Problems 2: Treatment Implementation and Attrition 11. Generalized Causal Inference: A Grounded Theory 12. Generalized Causal Inference: Methods for Single Studies 13. Generalized Causal Inference: Methods for Multiple Studies 14. A Critical Assessment of Our Assumptions