《Experimental and Quasi-Experimental Designs for Generalized Causal Inference》电子书下载

Experimental and Quasi-Experimental Designs for Generalized Causal Inferencetxt,chm,pdf,epub,mobi下载
作者:William R. Shadish/Thomas D. Cook/Donald T. Campbell
出版社: Cengage Learning
出版年: 2001-1-2
页数: 656
定价: USD 128.95
装帧: Paperback
ISBN: 9780395615560

内容简介 · · · · · ·

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:

目录 · · · · · ·

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

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
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