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Preface | p. xi |
The Challenge for Educational Research | p. 3 |
The Long Quest | p. 3 |
The Quest Is Worldwide | p. 9 |
What This Book Is About | p. 10 |
What to Read Next | p. 12 |
The Importance of Theory | p. 14 |
What Is Theory? | p. 15 |
Theory in Education | p. 19 |
Voucher Theory | p. 21 |
What Kind of Theories? | p. 24 |
What to Read Next | p. 24 |
Designing Research to Address Causal Questions | p. 26 |
Conditions to Strive for in All Research | p. 27 |
Making Causal Inferences | p. 29 |
Past Approaches to Answering Causal Questions in Education | p. 31 |
The Key Challenge of Causal Research | p. 33 |
What to Read Next | p. 39 |
Investigator-Designed Randomized Experiments | p. 40 |
Conducting Randomized Experiments | p. 41 |
The Potential Outcomes Framework | p. 41 |
An Example of a Two-Group Experiment | p. 45 |
Analyzing Data from Randomized Experiments | p. 48 |
The Better Your Research Design, the Simpler Your Data Analysis | p. 48 |
Bias and Precision in the Estimation of Experimental Effects | p. 52 |
What to Read Next | p. 60 |
Challenges in Designing, Implementing, and Learning from Randomized Experiments | p. 61 |
Critical Decisions in the Design of Experiments | p. 62 |
Defining the Treatment | p. 64 |
Defining the Population from Which Participants Will Be Sampled | p. 66 |
Deciding Which Outcomes to Measure | p. 67 |
Deciding How Long to Track Participants | p. 68 |
Threats to the Validity of Randomized Experiments | p. 69 |
Contamination of the Treatment-Control Contrast | p. 70 |
Cross-overs | p. 70 |
Attrition from the Sample | p. 71 |
Participation in an Experiment Itself Affects Participants' Behavior | p. 73 |
Gaining Support for Conducting Randomized Experiments: Examples from India | p. 74 |
Evaluating an Innovative Input Approach | p. 75 |
Evaluating an Innovative Incentive Policy | p. 79 |
What to Read Next | p. 81 |
Statistical Power and Sample Size | p. 82 |
Statistical Power | p. 83 |
Reviewing the Process of Statistical Inference | p. 83 |
Defining Statistical Power | p. 92 |
Factors Affecting Statistical Power | p. 96 |
The Strengths and Limitations of Parametric Tests | p. 101 |
The Benefits of Covariates | p. 102 |
The Reliability of the Outcome Measure Matters | p. 103 |
The Choice Between One-Tailed and Two-Tailed Tests | p. 105 |
What to Read Next | p. 106 |
Experimental Research When Participants Are Clustered Within Intact Groups | p. 107 |
Random-Intercepts Multilevel Model to Estimate Effect Size When Intact Groups Are Randomized to Experimental Conditions | p. 110 |
Statistical Power When Intact Groups of Participants Are Randomized to Experimental Conditions | p. 120 |
Statistical Power of the Cluster-Randomized Design and Intraclass Correlation | p. 122 |
Fixed-Effects Multilevel Models to Estimate Effects Size When Intact Groups of Participants Are Randomized to Experimental Conditions | p. 128 |
Specifying a Fixed-Effects Multilevel Model | p. 128 |
Choosing Between Random-and Fixed-Effects Specifications | p. 131 |
What to Read Next | p. 134 |
Using Natural Experiments to Provide "Arguably Exogenous" Treatment Variability | p. 135 |
Natural- and Investigator-Designed Experiments: Similarities and Differences | p. 136 |
Two Examples of Natural Experiments | p. 137 |
The Vietnam-Era Draft Lottery | p. 137 |
The Impact of an Offer of Financial Aid for College | p. 141 |
Sources of Natural Experiments | p. 145 |
Choosing the Width of the Analytic Window | p. 150 |
Threats to Validity in Natural Experiments with a Discontinuity Design | p. 152 |
Accounting for the Relationship Between the Outcome and the Forcing Variable in a Discontinuity Design | p. 153 |
Actions by Participants Can Undermine Exogenous Assignment to Experimental Conditions in a Natural Experiment with a Discontinuity Design | p. 163 |
What to Read Next | p. 164 |
Estimating Causal Effects Using a Regression-Discontinuity Approach | p. 165 |
Maimonides' Rule and the Impact of Class Size on Student Achievement | p. 166 |
A Simple First-Differences Analysis | p. 170 |
A Difference-in-Differences Analysis | p. 171 |
A Basic Regression-Discontinuity Analysis | p. 174 |
Choosing an Appropriate Bandwidth | p. 181 |
Generalizing the Relationship Between the Outcome and the Forcing Variable | p. 186 |
Specification Checks Using Pseudo-Outcomes and Pseudo-Cut-Offs | p. 192 |
Regression-Discontinuity Designs and Statistical Power | p. 195 |
Additional Threats to Validity in a Regression-Discontinuity Design | p. 197 |
What to Read Next | p. 202 |
Introducing Instrumental-Variables Estimation | p. 203 |
Introducing Instrumental-Variables Estimation | p. 204 |
Bias in the OLS Estimate of the Causal Effect of Education on Civic Engagement | p. 206 |
Instrumental-Variable Estimation | p. 215 |
Two Critical Assumptions That Underpin Instrumental-Variables Estimation | p. 223 |
Alternative Ways of Obtaining the Instrumental-Variables Estimate | p. 226 |
Obtaining an Instrumental-Variables Estimate by the Two-Stage Least-Squares Method | p. 227 |
Obtaining an Instrumental-Variables Estimate by Simultaneous-Equations Estimation | p. 233 |
Extensions of the Basic Instrumental-Variable Estimation Approach | p. 238 |
Incorporating Exogenous Covariates into Instrumental-Variable Estimation | p. 238 |
Incorporating Multiple Instruments into the First-Stage Model | p. 243 |
Examining the Impact of Interactions Between the Endogenous Question Predictor and Exogenous Covariates in the Second-Stage Model | p. 247 |
Choosing Appropriate Functional Forms for Outcome/Predictor Relationships in First- and Second-Stage Models | p. 251 |
Finding and Defending Instruments | p. 252 |
Proximity of Educational Institutions | p. 253 |
Institutional Rules and Personal Characteristics | p. 257 |
Deviations from Cohort Trends | p. 261 |
The Search Continues | p. 263 |
What to Read Next | p. 264 |
Using IVE to Recover the Treatment Effect in a Quasi-Experiment | p. 265 |
The Notion of a "Quasi-Experiment" | p. 267 |
Using IVE to Estimate the Causal Impact of a Treatment in a Quasi-Experiment | p. 269 |
Further Insight into the IVE (LATE) Estimate, in the Context of Quasi-Experimental Data | p. 274 |
Using IVE to Resolve "Fuzziness" in a Regression-Discontinuity Design | p. 280 |
What to Read Next | p. 285 |
Dealing with Bias in Treatment Effects Estimated from Nonexperimental Data | p. 286 |
Reducing Observed Bias by the Method of Stratification | p. 289 |
Stratifying on a Single Covariate | p. 289 |
Stratifying on Covariates | p. 299 |
Reducing Observed Bias by Direct Control for Covariates Using Regression Analysis | p. 304 |
Reducing Observed Bias Using a Propensity-Score Approach | p. 310 |
Estimation of the Treatment Effect by Stratifying on Propensity Scores | p. 316 |
Estimation of the Treatment Effect by Matching on Propensity Scores | p. 321 |
Estimation of the Treatment Effect by Weighting by the Inverse of the Propensity Scores | p. 324 |
A Return to the Substantive Question | p. 328 |
What to Read Next | p. 331 |
Methodological Lessons from the Long Quest | p. 332 |
Be Clear About Your Theory of Action | p. 333 |
Learn About Culture, Rules, and Institutions in the Research Setting | p. 335 |
Understand the Counterfactual | p. 337 |
Always Worry About Selection Bias | p. 338 |
Use Multiple Outcome Measures | p. 340 |
Be on the Lookout for Longer-Term Effects | p. 341 |
Develop a Plan for Examining Impacts on Subgroups | p. 342 |
Interpret Your Research Results Correctly | p. 344 |
Pay Attention to Anomalous Results | p. 346 |
Recognize That Good Research Always Raises New Questions | p. 348 |
What to Read Next | p. 349 |
Substantive Lessons and New Questions | p. 350 |
Lower the Cost of School Enrollment | p. 352 |
Reduce Commuting Time | p. 352 |
Reduce Out-of-Pocket Educational Costs | p. 353 |
Reduce Opportunity Costs | p. 354 |
Change Children's Daily Experiences in School | p. 355 |
More Books? | p. 355 |
Smaller Classes? | p. 356 |
Better Teaching? | p. 357 |
Improve Incentives | p. 359 |
Improve Incentives for Teachers | p. 359 |
Improve Incentives for Students | p. 361 |
Create More Schooling Options for Poor Children | p. 364 |
New Private-School Options | p. 365 |
New Public-School Options | p. 367 |
Summing Up | p. 367 |
Final Words | p. 368 |
References | p. 369 |
Index | p. 381 |
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