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Experimental and quasi-experimental designs for generalized causal inference / William R. Shadish, Thomas D. Cook & Donald T. Campbell.

By: Shadish, William R [autor.]Contributor(s): Cook, Thomas D | Campbell, Donald Thomas, 1916-1996Material type: TextTextLanguage: English Publisher: Belmon, California : Wadsworth, Cengage Learning, 2002Description: xxi, 623 páginas : ilustraciones, gráficas ; 24 cmContent type: texto Media type: sin mediación Carrier type: volumenISBN: 9780395615560Subject(s): Causalidad -- Investigaciones | Investigación cuantitativa | Diseño Experimental | Inferencia (Lógica) | Estadística matemática | MetafísicaDDC classification: 001.43
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 experimentals: 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. Generazed 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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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 experimentals: 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. Generazed 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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