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Summary
Table of Contents
| Preface | p. ix |
| What This Book Is About | p. 3 |
| What Is Program Evaluation? | p. 3 |
| Types of Program Evaluations | p. 8 |
| Basic Characteristics of Program Evaluation | p. 13 |
| Relation of Program Evaluation to the General Field of Policy Analysis | p. 15 |
| Assessing Government Performance: Program Evaluation and Performance Measurement | p. 15 |
| A Brief History of Program Evaluation | p. 17 |
| What Comes Next | p. 19 |
| Key Concepts | p. 20 |
| Do It Yourself | p. 20 |
| Defensible Program Evaluations: Four Types of Validity | p. 26 |
| Defining Defensibility | p. 26 |
| Types of Validity: Definitions | p. 27 |
| Types of Validity: Threats and Simple Remedies | p. 28 |
| Basic Concepts | p. 47 |
| Do It Yourself | p. 48 |
| Internal Validity | p. 51 |
| The Logic of Internal Validity | p. 51 |
| Making Comparisons: Cross Sections and Time Series | p. 54 |
| Threats to Internal Validity | p. 55 |
| Summary | p. 63 |
| Three Basic Research Designs | p. 64 |
| Rethinking Validity: The Causal Model Workhorse | p. 66 |
| Basic Concepts | p. 68 |
| Do It Yourself | p. 69 |
| A Summary of Threats to Internal Validity | p. 70 |
| Randomized Field Experiments | p. 73 |
| Basic Characteristics | p. 73 |
| Brief History | p. 74 |
| Caveats and Cautions About Randomized Experiments | p. 76 |
| Types of RFEs | p. 79 |
| Issues in Implementing RFEs | p. 92 |
| Threats to the Validity of RFEs: Internal Validity | p. 96 |
| Threats to the Validity of RFEs: External Validity | p. 100 |
| Threats to the Validity of RFEs: Measurement and Statistical Validity | p. 101 |
| Conclusion | p. 101 |
| Some Cool Examples of RFEs | p. 102 |
| Basic Concepts | p. 103 |
| Do It Yourself: Design a Randomized Field Experiment | p. 104 |
| The Quasi Experiment | p. 110 |
| Defining Quasi-Experimental Designs | p. 110 |
| The One-Shot Case Study | p. 111 |
| The Posttest-Only Comparison-Group (PTCG) Design | p. 113 |
| The Pretest-Posttest Comparison-Group (PTPTCG) (The Nonequivalent Control-Group) Design | p. 119 |
| The Pretest-Posttest (Single-Group) Design | p. 123 |
| The Single Interrupted Time-Series Design | p. 125 |
| The Interrupted Time-Series Comparison-Group (TTSCG) Design | p. 131 |
| The Multiple Comparison-Group Time-Series Design | p. 134 |
| Summary of Quasi-Experimental Design | p. 135 |
| Basic Concepts | p. 136 |
| Do It Yourself | p. 137 |
| The Nonexperimental Design: Variations on the Multiple Regression Theme | p. 143 |
| What Is a Nonexperimental Design? | p. 143 |
| Back to the Basics: The Workhorse Diagram | p. 144 |
| The Nonexperimental Workhorse Regression Equation | p. 146 |
| Data for the Workhorse Regression Equation | p. 148 |
| Interpreting Multiple Regression Output | p. 149 |
| Assumptions Needed to Believe That b Is a Valid Estimate of B [E(b) = B] | p. 164 |
| Assumptions Needed to Believe the Significance Test for b | p. 184 |
| What Happened to the R2? | p. 190 |
| Conclusion | p. 191 |
| Basic Concepts | p. 192 |
| Introduction to Stata | p. 194 |
| Do It Yourself: Interpreting Nonexperimental Results | p. 197 |
| Designing Useful Surveys for Evaluation | p. 209 |
| The Response Rate | p. 210 |
| How to Write Questions to Get Unbiased, Accurate, Informative Responses | p. 217 |
| Turning Responses into Useful Information | p. 224 |
| For Further Reading | p. 233 |
| Basic Concepts | p. 233 |
| Do It Yourself | p. 234 |
| Summing It Up: Meta-Analysis | p. 239 |
| What Is Meta-Analysis? | p. 239 |
| Example of a Meta-Analysis: Data | p. 240 |
| Example of a Meta-Analysis: Variables | p. 241 |
| Example of a Meta-Analysis: Data Analysis | p. 242 |
| The Role of Meta-Analysis in Program Evaluation and Causal Conclusions | p. 243 |
| For Further Reading | p. 244 |
| Index | p. 247 |
| About the Author | p. 253 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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