Quasi-Experimentation: A Guide to Design and Analysis (Paperback)

1. IntroductionOverview1.1 Introduction1.2 The Definition of Quasi-Experiment1.3 Why Study Quasi-Experiments1.4 Overview of the Volume1.5 Conclusions1.6 Suggested Reading2. Cause and EffectOverview2.1 Introduction2.2 Practical Comparisons and Confounds2.3 The Counterfactual Definition2.4 The Stable-Unit-Treatment-Value Assumption (SUTVA)2.5 The Causal Question Being Addressed2.6 Conventions2.7 Conclusions2.8 Suggested Reading3. Threats to ValidityOverview3.1 Introduction3.2 The Size of an Effect3.3 Construct Validity3.4 Internal Validity3.5 Statistical Conclusion Validity3.6 External Validity3.7 Trade-offs among Types of Validity3.8 A Focus on Internal and Statistical Conclusion Validity3.9 Conclusions3.10 Suggested Reading4. Randomized ExperimentsOverview4.1 Introduction4.2 Between-Groups Randomized Experiments4.3 Examples of Randomized Experiments Conducted in the Field4.4 Selection Differences4.5 Analysis of Data from the Posttest-Only Randomized Experiment4.6 Analysis of Data from the Pretest?Posttest Randomized Experiment4.7 Noncompliance with Treatment Assignment4.8 Missing Data and Attrition4.9 Cluster-Randomized Experiments4.10 Other Threats to Validity in Randomized Experiments4.11 Strengths and Weaknesses4.12 Conclusions4.13 Suggested Reading5. One-Group Posttest-Only DesignsOverview5.1 Introduction5.2 Examples of One-Group Posttest-Only Designs5.3 Strengths and Weaknesses5.4 Conclusions5.5 Suggested Reading6. Pretest?Posttest DesignsOverview6.1 Introduction6.2 Examples of Pretest?Posttest Designs6.3 Threats to Internal Validity6.4 Design Variations6.5 Strengths and Weaknesses6.6 Conclusions6.7 Suggested Reading7. Nonequivalent Group DesignsOverview7.1 Introduction7.2 Two Basic Nonequivalent Group Designs7.3 Change-Score Analysis7.4 Analysis of Covariance7.5 Matching and Blocking7.6 Propensity Scores7.7 Instrumental Variables7.8 Selection Models7.9 Sensitivity Analyses and Tests of Ignorability7.10 Other Threats to Internal Validity besides Selection Differences7.11 Alternative Nonequivalent Group Designs7.12 Empirical Evaluations and Best Practices7.13 Strengths and Weaknesses7.14 Conclusions7.15 Suggested Reading8. Regression Discontinuity DesignsOverview8.1 Introduction8.2 The Quantitative Assignment Variable8.3 Statistical Analysis8.4 Fuzzy Regression Discontinuity8.5 Threats to Internal Validity8.6 Supplemented Designs8.7 Cluster Regression Discontinuity Designs8.8 Strengths and Weaknesses8.9 Conclusions8.10 Suggested Reading9. Interrupted Time-Series DesignsOverview9.1 Introduction9.2 The Temporal Pattern of the Treatment Effect9.3 Two Versions of the Design9.4 The Statistical Analysis of Data When N = 19.5 The Statistical Analysis of Data When N Is Large9.6 Threats to Internal Validity9.7 Design Supplements I: Multiple Interventions9.8 Design Supplements II: Basic Comparative ITS Designs9.9 Design Supplements III: Comparative ITS Designs with Multiple Treatments9.10 Single-Case Designs9.11 Strengths and Weaknesses9.12 Conclusions9.13 Suggested Reading10. A Typology of ComparisonsOverview10.1 Introduction10.2 The Principle of Parallelism10.3 Comparisons across Participants10.4 Comparisons across Times10.5 Comparisons across Settings10.6 Comparisons across Outcome Measures10.7 Within- and Between-Subject Designs10.8 A Typology of Comparisons10.9 Random Assignment to Treatment Conditions10.10 Assignment to Treatment Conditions Based on an Explicit Quantitative Ordering10.11 Nonequivalent Assignment to Treatment Conditions10.12 Credibility and Ease of Implementation10.13 The Most Commonly Used Comparisons10.14 Conclusions10.15 Suggested Reading11. Methods of Design ElaborationOverview11.1 Introduction11.2 Three Methods of Design Elaboration11.3 The Four Size-of-Effect Factors as Sources for the Two Estimates in Design Elaboration11.4 Conclusions 11.5 Suggested Reading12. Unfocused Design Elaboration and Pattern MatchingOverview12.1 Introduction12.2 Four Examples of Unfocused Design Elaboration12.3 Pattern Matching12.4 Conclusions12.5 Suggested Reading13. Principles of Design and Analysis for Estimating EffectsOverview13.1 Introduction13.2 Design Trumps Statistics13.3 Customized Designs13.4 Threats to Validity13.5 The Principle of Parallelism13.6 The Typology of Simple Comparisons13.7 Pattern Matching and Design Elaborations13.8 Size of Effects13.9 Bracketing Estimates of Effects13.10 Critical Multiplism13.11 Mediation13.12 Moderation13.13 Implementation13.14 Qualitative Research Methods13.15 Honest and Open Reporting of Results13.16 Conclusions13.17 Suggested ReadingAppendix: The Problems of Overdetermination and PreemptionA.1 The Problem of OverdeterminationA.2 The Problem of PreemptionReferencesGlossaryAuthor IndexSubject IndexAbout the Author