Public Program Evaluation

Public Program Evaluation : A Statistical Guide

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First Published in 2007. Routledge is an imprint of Taylor & Francis, an Informa company.
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Product details

  • Hardback | 290 pages
  • 182.9 x 251.5 x 20.3mm | 635.04g
  • Taylor & Francis Inc
  • M.E. Sharpe
  • Armonk, United States
  • English
  • tables, figures, references, index
  • 0765613662
  • 9780765613660

Table of contents

1. What This Book Is About; What Is Program Evaluation?; * Types of Program Evaluations; * Basic Characteristics of Program Evaluation; * Relation of Program Evaluation to General Field of Policy Analysis; * Assessing Government Performance: Program Evaluation and GPRA; * A Brief History of Program Evaluation; * What Comes Next; * Key Concepts; * Do It Yourself; 2. Performance Measurement and Benchmarking; Program Evaluation and Performance Measurement: What Is the Difference?; * Benchmarking; * Reporting Performance Results; * Conclusion; * Exercise: Try It Yourself!; 3. Defensible Program Evaluations: Four Types of Validity; Defining "Defensibility"; * Types of Validity: Definitions; * Types of Validity: Threats and Simple Remedies; * Basic Concepts; * Do It Yourself; 4. Internal Validity; The Logic of Internal Validity; * Making Comparisons: Cross-Sections and Time Series; * Threats to Internal Validity; * Summary; * Three Basic Research Designs; * Rethinking Validity: The Causal Model Workhorse; * Basic Concepts; * Exercise: Try It Yourself; * A Summary to Help; 5. Randomized Field Experiments; Basic Characteristics; * Brief History; * Caveats and Cautions about Randomized Experiments; * Types of RFEs; * Issues in Implementing RFEs; * Threats to the Validity of RFEs: Internal Validity; * Threats to the Validity of RFEs: External Validity; * Threats to the Validity of RFEs: Measurement and Statistical Validity; * Conclusion; * Three Cool Examples of RFEs; * Basic Concepts; * Do It Yourself: Design a Randomized Field Experiment; 6. The Quasi-Experiment; Defining Quasi-Experimental Designs; * The One-Shot Case Study; * The Post-Test Only Comparison Group (PTCG); * The Pre-Test Post-Test Comparison Group (a.k.a. The Non-Equivalent Control Group); * The Pre-Test Post-Test (Single Group) Design; * Single Interrupted Time-Series Design; * The Interrupted Time-Series Comparison Group Design (TTSCG); * The Multiple Comparison Group Time-Series Design; * Summary of Quasi-Experimental Design; * Basic Concepts; * Do It Yourself; 7. The Non-Experimental Design: Variations on the Multiple Regression Theme; What Is a Non-Experimental Design?; * Back to Basics: The Workhorse Diagram; * The Non-Experimental Workhorse Regression Equation; * Data for the Workhorse Regression Equation; * Interpreting Multiple Regression Output; * Assumptions Needed to Believe That b is Valid Estimate of B (E(b) = B); * Assumptions Needed to Believe the Significance Test for b; * What Happened to the R2?; * Conclusion; * Basic Concepts; * Introduction to STATA; * Do It Yourself; 8. Designing Useful Surveys for Evaluation; Introduction; * The Response Rate; * How to Write Questions to Get Unbiased, Accurate, Informative Responses; * Turning Responses into Useful Information; * For Further Reading; * Basic Concepts; * On Your Own; 9. Summing It Up: Meta-Analysis; What Is Meta-Analysis?; * Example of a Meta-Analysis: Data; * Example of a Meta-Analysis: Variables; * Example of a Meta-Analysis: Data Analysis; * The Role of Meta-Analysis in Program Evaluation and Causal Conclusions; * Conclusions; * For Further Reading; Notes; * About the Authors; * Index.
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