Preface |
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xxix | |
Acknowledgments |
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xxxiii | |
About the Authors |
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xxxv | |
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1 | (92) |
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2 | (1) |
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1 Research in the Real World |
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3 | (22) |
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3 | (2) |
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Good Evidence Comes From Well-Made Research |
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3 | (1) |
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4 | (1) |
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Research-Savvy People Rule |
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4 | (1) |
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Research, Policy, and Practice |
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5 | (1) |
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5 | (1) |
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5 | (1) |
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Evidence-Based Policy and Programs |
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6 | (1) |
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6 | (1) |
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6 | (1) |
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6 | (1) |
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7 | (1) |
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7 | (4) |
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Secondary and Primary Research |
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7 | (1) |
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It Comes in Various Shapes and Sizes |
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8 | (1) |
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8 | (1) |
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It's Uncertain and Contingent |
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8 | (1) |
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9 | (1) |
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Bits and Pieces of a Puzzle |
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9 | (1) |
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It Involves Competition and Criticism |
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10 | (1) |
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It Can Be Quantitative, Qualitative, or a Mix of Both |
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10 | (1) |
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It Can Be Applied or Basic |
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10 | (1) |
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Descriptive and Causal Research |
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11 | (1) |
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Description: What Is the World Like? |
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11 | (1) |
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Causation: How Would the World Be Different If Something Changed? |
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12 | (1) |
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Description of a Correlation Is Not Proof of Causation |
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12 | (1) |
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Epistemology: Ways of Knowing |
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12 | (3) |
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13 | (1) |
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Is There One Truth in Social Science? |
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13 | (1) |
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14 | (1) |
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Proof Requires Fresh Data |
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14 | (1) |
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Approaching Research From Different Angles |
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15 | (2) |
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15 | (1) |
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16 | (1) |
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16 | (1) |
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17 | (4) |
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Poisoned by New York's Best Restaurants |
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17 | (1) |
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History of Human Subjects Abuses in Research |
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18 | (1) |
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Principles of Ethical Research Emerge |
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18 | (1) |
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What Constitutes Informed Consent? |
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19 | (1) |
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Ethical Issues Depend on Research Form and Context |
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20 | (1) |
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Conclusion: The Road Ahead |
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21 | (1) |
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21 | (3) |
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21 | (1) |
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21 | (2) |
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23 | (1) |
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24 | (1) |
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2 Theory, Models, and Research Questions |
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25 | (34) |
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Fighting Crime in New York City |
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25 | (1) |
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26 | (2) |
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Theories Identify Key Variables |
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26 | (1) |
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Theories Tell Causal Stories |
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26 | (1) |
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Theories Explain Variation |
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27 | (1) |
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Theories Generate Testable Hypotheses |
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28 | (1) |
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Theories Focus on Modifiable Variables |
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28 | (1) |
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Where Do Theories Come From? |
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28 | (2) |
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28 | (1) |
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29 | (1) |
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29 | (1) |
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Exploratory and Qualitative Research |
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29 | (1) |
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Theories, Norms, and Values |
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30 | (1) |
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30 | (6) |
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Variables and Relationships |
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30 | (1) |
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Independent and Dependent Variables |
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31 | (1) |
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Box 2.1 Independent And Dependent Variables |
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32 | (1) |
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32 | (1) |
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Box 2.2 Equations As Models: Right-Hand Side And Left-Hand Side Variables |
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33 | (1) |
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Direction of a Relationship |
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33 | (1) |
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34 | (1) |
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Models With Multiple Causes |
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35 | (1) |
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Causal and Noncausal Relationships |
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35 | (1) |
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36 | (2) |
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Same Theory, Different Unit of Analysis |
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36 | (2) |
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38 | (7) |
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Box 2.3 What Is A Logic Model? |
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38 | (1) |
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Do Smaller Classes Help Kids Learn? |
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39 | (1) |
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40 | (1) |
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41 | (1) |
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Usefulness of a Logic Model |
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41 | (1) |
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Box 2.4 China Launches Nationwide Aids Prevention Program |
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42 | (1) |
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Tips for Creating a Logic Model |
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43 | (2) |
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Inputs, Activities, Outputs, and Outcomes |
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45 | (2) |
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Additional Issues in Theory Building |
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47 | (2) |
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47 | (1) |
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Does Theory Shape Observation? |
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47 | (1) |
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Theories of the Independent Variable |
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47 | (1) |
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48 | (1) |
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Hierarchical (Multilevel) Models and Contextual Variables |
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48 | (1) |
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49 | (1) |
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How to Find and Focus Research Questions |
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49 | (3) |
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Applied Research Questions |
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49 | (1) |
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Questions You Ideally Want to Answer, and Those You Really Can |
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50 | (1) |
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Know If Your Question Is Descriptive or Causal |
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51 | (1) |
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Make Your Question Positive, Not Normative |
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51 | (1) |
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Generating Questions and Ideas |
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51 | (1) |
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Conclusion: Theories Are Practical |
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52 | (2) |
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Box 2.5 Critical Questions To Ask About Theory, Models, And Research Questions |
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53 | (1) |
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Box 2.6 Tips On Doing Your Own Research: Theory, Models, And Research Questions |
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53 | (1) |
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54 | (4) |
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54 | (1) |
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54 | (2) |
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56 | (2) |
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58 | (1) |
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59 | (34) |
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Fighting Malaria in Kenya |
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59 | (2) |
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Theory, Causes, and Qualitative Research |
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60 | (1) |
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What Is Qualitative Research? |
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61 | (4) |
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Contrasting Qualitative With Quantitative Research |
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61 | (2) |
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Schools of Thought in Qualitative Research |
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63 | (1) |
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Advantages of Qualitative Research |
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64 | (1) |
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Existing Qualitative Data |
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65 | (2) |
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Archival and Other Written Documents |
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66 | (1) |
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Visual Media, Popular Culture, and the Internet |
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66 | (1) |
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67 | (3) |
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67 | (1) |
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Semistructured Interviews |
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67 | (2) |
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Asking Truly Open-Ended Questions |
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69 | (1) |
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69 | (1) |
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Some Practical Considerations When Doing Interviews |
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70 | (1) |
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70 | (3) |
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What Do People Think of Congestion Pricing? |
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71 | (1) |
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72 | (1) |
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Why a Focus Group? Why Not Individual Interviews? |
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73 | (1) |
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Telephone and Online Focus Groups |
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73 | (1) |
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73 | (1) |
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Participant Observation and Ethnography |
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74 | (2) |
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Why Do the Homeless Refuse Help? |
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74 | (1) |
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Levels on a Participation-Observation Continuum |
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75 | (1) |
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Secret Shopping and Audit Studies |
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75 | (1) |
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76 | (1) |
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Maryland's Gun Violence Act |
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76 | (1) |
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Selecting a Case to Study |
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77 | (1) |
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77 | (1) |
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Qualitative Data Analysis |
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77 | (5) |
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Integration of Analysis and Data Gathering |
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78 | (1) |
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Tools of Qualitative Analysis |
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78 | (1) |
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Coding and Content Analysis |
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79 | (2) |
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Qualitative Data Analysis Software |
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81 | (1) |
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The Qualitative-Quantitative Debate |
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82 | (5) |
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A Brief History of the Debate |
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82 | (1) |
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Blurring the Lines: How Qualitative and Quantitative Approaches Overlap |
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83 | (1) |
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A Qualitative-Quantitative Research Cycle |
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83 | (3) |
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Mixed-Methods Research and Triangulation |
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86 | (1) |
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Box 3.1 Transition Services For Incarcerated Youth: A Mixed Methods Evaluation Study |
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86 | (1) |
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Ethics in Qualitative Research |
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87 | (1) |
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Presenting Qualitative Data |
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87 | (1) |
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Can You Obtain Informed Consent? |
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87 | (1) |
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Should You Help People With Their Problems? |
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87 | (1) |
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Should You Empower People? |
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88 | (1) |
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Conclusion: Matching Methods to Questions |
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88 | (2) |
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Box 3.2 Critical Questions To Ask About A Qualitative Study |
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89 | (1) |
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Box 3.3 Tips On Doing Your Own Qualitative Research |
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89 | (1) |
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90 | (3) |
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90 | (1) |
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90 | (2) |
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92 | (1) |
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PART II STRATEGIES FOR DESCRIPTION |
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93 | (148) |
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94 | (1) |
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95 | (46) |
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95 | (1) |
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95 | (2) |
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Measurement in Qualitative Research |
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96 | (1) |
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96 | (1) |
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Measurement: The Basic Model and a Road Map |
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96 | (1) |
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97 | (3) |
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Defining Can Be Difficult |
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97 | (1) |
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Where Do Conceptualizations Come From? |
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98 | (1) |
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Box 4.1 Is Poverty The Same Thing The World Over? |
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98 | (1) |
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Manifest and Latent Constructs |
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99 | (1) |
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99 | (1) |
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100 | (6) |
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Birth of the U.S. Poverty Measure |
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100 | (1) |
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101 | (1) |
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Box 4.2 Operational Definition Of Poverty In The United States |
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101 | (1) |
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102 | (1) |
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102 | (1) |
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Composite Measures: Scales and Indexes |
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103 | (2) |
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Box 4.3 What Is A Likert Scale? |
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105 | (1) |
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106 | (4) |
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Box 4.4 Using Items That Vary In Difficulty: Item Response Theory |
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107 | (1) |
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Is the U.S. Poverty Measure Valid? |
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107 | (1) |
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108 | (1) |
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108 | (1) |
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109 | (1) |
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Criterion-Related Validity |
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110 | (4) |
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Self-Reported Drug Use: Is It Valid? |
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110 | (1) |
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Does the Measure Predict Behavior? |
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110 | (1) |
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Does the Measure Relate to Other Variables as Expected? |
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111 | (1) |
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Limitations of Validity Studies |
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112 | (1) |
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Box 4.5 The Various (Measurement) Validities |
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113 | (1) |
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Box 4.6 Example Of A Validity Study |
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114 | (1) |
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114 | (4) |
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115 | (1) |
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115 | (1) |
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Box 4.7 Bias, Bias Everywhere |
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116 | (1) |
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Bias and Noise in the U.S. Poverty Measure |
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116 | (1) |
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Box 4.8 Classical Test Theory |
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117 | (1) |
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118 | (6) |
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118 | (3) |
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Many Ways to Tell If a Measure Is Reliable |
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121 | (1) |
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Validity and Reliability Contrasted and Compared |
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122 | (2) |
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Validity and Reliability in Qualitative Research |
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124 | (1) |
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124 | (7) |
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125 | (1) |
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Box 4.9 Unit/Level Of Measurement/Analysis? |
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126 | (1) |
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126 | (2) |
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Turning Categorical Variables Into Quantitative Ones |
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128 | (2) |
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Units of Analysis and Levels of Measurement |
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130 | (1) |
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Measurement in the Real World: Trade-offs and Choices |
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131 | (4) |
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131 | (1) |
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131 | (1) |
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How Will It Affect the Quality and Rate of Responding? |
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131 | (1) |
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Validity-Reliability Trade-off |
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132 | (1) |
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High Stakes? Gaming and Other Behavioral Responses |
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133 | (1) |
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Use Multiple Measures for Multiple Dimensions---or Aggregate to One Measure? |
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133 | (1) |
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Conclusion: Measurement Matters |
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134 | (1) |
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Box 4.10 Critical Questions To Ask About Measurement |
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134 | (1) |
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Box 4.11 Tips On Doing Your Own Research: Measurement |
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135 | (1) |
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135 | (5) |
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135 | (1) |
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136 | (3) |
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139 | (1) |
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140 | (1) |
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141 | (40) |
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Gauging the Fallout From Hurricane Katrina |
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141 | (1) |
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141 | (4) |
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Population of Interest, Sampling, and Generalizability |
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142 | (1) |
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Are Experiments More Generalizable? |
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143 | (1) |
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Replicating Research and Meta-Analysis |
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143 | (1) |
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Are Relationships More Generalizable? Health and Happiness in Moldova |
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144 | (1) |
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Generalizability of Qualitative Studies |
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145 | (1) |
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145 | (4) |
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Population, Sample, and Inference |
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145 | (2) |
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147 | (1) |
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How to Select a Sample: Sampling Frames and Steps |
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148 | (1) |
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Problems and Biases in Sampling |
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149 | (5) |
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149 | (1) |
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150 | (1) |
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When Does Nonresponse Cause Bias? |
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150 | (2) |
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When Do Coverage Problems Cause Bias? |
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152 | (1) |
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Box 5.1 Steps In Assessing Coverage And Nonresponse Bias |
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153 | (1) |
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154 | (1) |
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154 | (1) |
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154 | (5) |
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155 | (1) |
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Box 5.3 Steps In Assessing Volunteer Bias |
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155 | (1) |
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156 | (1) |
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156 | (1) |
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156 | (1) |
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Sampling Online: Open Web Polls and Internet Access Panels |
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156 | (2) |
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Purposive Sampling and Qualitative Research |
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158 | (1) |
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Random (Probability) Sampling |
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159 | (2) |
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The Contribution of Random Sampling |
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159 | (1) |
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Random Sampling Versus Randomized Experiments |
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160 | (1) |
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160 | (1) |
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161 | (1) |
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Sampling Distributions, Standard Errors, and Confidence Intervals |
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161 | (7) |
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Confidence Intervals (Margins of Error) |
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162 | (1) |
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Box 5.4 Relationship Between Various Precision Measures |
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163 | (2) |
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Sample Size and the Precision of Government Statistics |
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165 | (1) |
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Determining How Large a Sample You Need |
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165 | (2) |
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What Is the True Sample Size? |
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167 | (1) |
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168 | (6) |
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168 | (1) |
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168 | (1) |
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Disproportionate Sampling (Oversampling) |
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169 | (1) |
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Poststratification Weighting |
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170 | (1) |
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Sampling With Probabilities Proportional to Size |
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171 | (1) |
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Multistage and Cluster Sampling |
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171 | (1) |
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Design Effects: Complex Survey Sampling Corrections |
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172 | (1) |
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Random Digit Dialing Sampling |
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173 | (1) |
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Sampling and Generalizability: A Summary |
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174 | (2) |
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Box 5.5 Critical Questions To Ask About Sampling In Studies |
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174 | (1) |
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Box 5.6 Tips On Doing Your Own Research: Sampling |
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175 | (1) |
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176 | (4) |
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176 | (1) |
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176 | (3) |
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179 | (1) |
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180 | (1) |
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181 | (30) |
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181 | (1) |
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Big Data and the Virtual World |
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182 | (1) |
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Quantitative Data---and Their Forms |
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182 | (6) |
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Quantitative Data Versus Quantitative Variables |
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182 | (1) |
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Forms of Quantitative Data |
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183 | (1) |
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Micro, Aggregate, and Multilevel Data |
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184 | (1) |
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Box 6.1 Unit Of Observation Versus Unit Of Analysis |
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184 | (1) |
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184 | (2) |
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186 | (2) |
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Where Do Quantitative Data Come From? |
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188 | (1) |
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188 | (3) |
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Adapting Administrative Data for Research |
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188 | (2) |
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Vital Statistics, Crime Reports, and Unemployment Claims |
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190 | (1) |
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190 | (1) |
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Ethics of Administrative Record Data |
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191 | (1) |
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191 | (3) |
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Where to Find Published Tables |
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194 | (1) |
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Published Time-Series and Panel Data |
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194 | (1) |
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194 | (9) |
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Secondary Analysis of Public Use Data: A New Model of Research? |
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194 | (1) |
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Know the Major Surveys in Your Field |
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195 | (7) |
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Accessing and Analyzing Public Use Data |
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202 | (1) |
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202 | (1) |
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Ethics of Public Use Microdata |
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203 | (1) |
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Secondary Qualitative Data |
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203 | (1) |
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204 | (1) |
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Some Limitations of Secondary Data |
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204 | (2) |
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Does Data Availability Distort Research? |
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205 | (1) |
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When to Collect Original Data? |
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205 | (1) |
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206 | (1) |
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Box 6.2 Critical Questions To Ask About Secondary Data |
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206 | (1) |
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Box 6.3 Tips On Doing Your Own Research: Secondary Data |
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206 | (1) |
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207 | (3) |
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207 | (1) |
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207 | (2) |
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209 | (1) |
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210 | (1) |
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7 Surveys and Other Primary Data |
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211 | (30) |
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Taking the Nation's Economic Pulse |
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211 | (1) |
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When Should You Do a Survey? |
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211 | (2) |
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Do You Know Enough About the Topic? |
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212 | (1) |
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Does the Information Exist Already in Another Source? |
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212 | (1) |
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Can People Tell You What You Want to Know? |
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212 | (1) |
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Will People Provide Truthful Answers? |
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213 | (1) |
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Steps in the Survey Research Process |
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213 | (2) |
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Identify the Population and Sampling Strategy |
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213 | (1) |
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213 | (1) |
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Pretest Questionnaire and Survey Procedures |
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214 | (1) |
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Recruit and Train Interviewers |
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214 | (1) |
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214 | (1) |
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Enter and Prepare Data for Analysis |
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215 | (1) |
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Analyze Data and Present Findings |
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215 | (1) |
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Modes of Survey Data Collection |
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215 | (9) |
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Intercept Interview Surveys |
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215 | (1) |
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Household Interview Surveys |
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216 | (1) |
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Telephone Interview Surveys |
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217 | (1) |
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Mail Self-Administered Surveys |
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218 | (2) |
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Group Self-Administered Surveys |
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220 | (1) |
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220 | (1) |
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Box 7.1 Web Survey Software |
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221 | (1) |
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Establishment (Business or Organization) Surveys |
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222 | (1) |
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Panel or Longitudinal Surveys |
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222 | (1) |
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223 | (1) |
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224 | (7) |
|
Start With Survey Purpose or Constructs |
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224 | (1) |
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If You Could Ask Only One or Two Questions. . . |
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224 | (1) |
|
Prepare Mock Tables and Charts of Survey Results |
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224 | (1) |
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Look for Prior Surveys on Your Topic |
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|
224 | (1) |
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Hook Respondents With Your First Few Questions |
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225 | (1) |
|
Box 7.2 Comparing Opening Questions |
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225 | (1) |
|
Closed-Ended Versus Open-Ended Questions |
|
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226 | (1) |
|
Box 7.3 Questionnaire Composed Of Open-Ended Questions |
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227 | (1) |
|
Some Advice on Question Wording |
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227 | (3) |
|
Physical and Graphical Design |
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230 | (1) |
|
Put Yourself in Your Respondent's Shoes |
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230 | (1) |
|
Ethics of Survey Research |
|
|
231 | (1) |
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|
231 | (1) |
|
Pushing for a High Response Rate |
|
|
231 | (1) |
|
Overburdening Respondents |
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|
231 | (1) |
|
Protecting Privacy and Confidentiality |
|
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231 | (1) |
|
Surveying Minors and Other Vulnerable Populations |
|
|
232 | (1) |
|
Making Survey Data Available for Public Use |
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|
232 | (1) |
|
Other Ways to Collect Primary Data |
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232 | (4) |
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|
233 | (2) |
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|
235 | (1) |
|
Computer Code and Data Extraction Algorithms |
|
|
236 | (1) |
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|
236 | (2) |
|
Box 7.4 Critical Questions To Ask About Surveys And Other Primary Data |
|
|
236 | (1) |
|
Box 7.5 Tips On Doing Your Own Survey |
|
|
237 | (1) |
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|
238 | (3) |
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|
238 | (1) |
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|
238 | (1) |
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|
239 | (2) |
|
PART III STATISTICAL TOOLS AND THEIR INTERPRETATION |
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|
241 | (106) |
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242 | (1) |
|
8 Making Sense of the Numbers |
|
|
243 | (38) |
|
"Last Weekend I Walked Eight" |
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|
243 | (1) |
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|
243 | (5) |
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243 | (1) |
|
Rates or Why Counts Often Mislead |
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|
244 | (1) |
|
Box 8.1 Relevant Comparisons |
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|
245 | (1) |
|
Percent Change and Percentage Point Change |
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245 | (1) |
|
The Strangeness of Percent Change on the Return Trip |
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|
246 | (1) |
|
Rates of Change and Rates of Change of Rates |
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246 | (1) |
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247 | (1) |
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247 | (1) |
|
Statistics Starting Point: Variables in a Data Set |
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248 | (1) |
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249 | (3) |
|
Distribution of a Categorical Variable |
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249 | (2) |
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Distribution of a Quantitative Variable |
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251 | (1) |
|
Measures of Center: Mean and Median |
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|
252 | (1) |
|
Box 8.2 Mean: The Formula |
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|
252 | (1) |
|
When to Use Median? When to Use Mean? |
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|
253 | (1) |
|
Measures of Spread and Variation |
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|
253 | (4) |
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|
254 | (1) |
|
Box 8.3 Standard Deviation: The Formula |
|
|
254 | (1) |
|
Pay Attention to the Standard Deviation, Not Just the Mean |
|
|
255 | (1) |
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|
255 | (1) |
|
Quantiles: Another Way to Measure Spread |
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256 | (1) |
|
Coefficient of Variation: A Way to Compare Spread |
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|
256 | (1) |
|
Relationships Between Categorical Variables |
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|
257 | (3) |
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|
257 | (2) |
|
Relative Risks and Odds Ratios: Another Way to Show Relationships in Categorical Data |
|
|
259 | (1) |
|
Adjusted and Standardized Rates: When to Use Them |
|
|
260 | (1) |
|
Relationships Between Quantitative Variables: Scatterplots and Correlation |
|
|
260 | (4) |
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|
260 | (2) |
|
|
262 | (1) |
|
Box 8.4 Correlation: The Formula |
|
|
262 | (1) |
|
Relationships Between a Categorical and a Quantitative Variable |
|
|
263 | (1) |
|
Box 8.5 Which One Is The Dependent Variable? Which One Is The Independent Variable? |
|
|
264 | (1) |
|
Simple Regression: Best-Fit Straight Line |
|
|
264 | (5) |
|
Box 8.6 Simple Regression: The Equations |
|
|
265 | (1) |
|
Interpreting the Regression Coefficient (Slope) |
|
|
266 | (1) |
|
Box 8.7 Steps For Interpreting A Regression Coefficient |
|
|
266 | (1) |
|
Can a Regression Coefficient Be Interpreted as a Causal Effect? |
|
|
267 | (1) |
|
|
267 | (1) |
|
R-Squared and Residuals: How Well Does the Line Fit the Data? |
|
|
268 | (1) |
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|
269 | (2) |
|
Practical Significance Is a Matter of Judgment |
|
|
269 | (1) |
|
|
270 | (1) |
|
|
271 | (1) |
|
|
271 | (1) |
|
Statistical Packages: SAS, SPSS, Stata, and R |
|
|
271 | (1) |
|
Specialized Modeling and Matrix Language Programs |
|
|
271 | (1) |
|
Conclusion: Tools for Description and Causation |
|
|
271 | (2) |
|
Box 8.8 Tips On Doing Your Own Research: Descriptive Statistics |
|
|
272 | (1) |
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|
273 | (7) |
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|
273 | (1) |
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|
273 | (6) |
|
|
279 | (1) |
|
|
280 | (1) |
|
9 Making Sense of Inferential Statistics |
|
|
281 | (32) |
|
|
281 | (1) |
|
Statistical Inference: What's It Good For? |
|
|
281 | (1) |
|
The Sampling Distribution: Foundation of Statistical Inference |
|
|
282 | (3) |
|
What a Sampling Distribution Looks Like |
|
|
282 | (2) |
|
The Standard Error (of a Proportion) |
|
|
284 | (1) |
|
The Standard Error (of a Mean) |
|
|
285 | (1) |
|
|
285 | (6) |
|
Univariate Statistics and Relationships Both Have Confidence Intervals |
|
|
286 | (1) |
|
Confidence Intervals Reflect Only Some Sources of Error |
|
|
287 | (1) |
|
Calculating a Confidence Interval (Margin of Error) for a Proportion |
|
|
287 | (1) |
|
Calculating a Confidence Interval (Margin of Error) for a Mean |
|
|
288 | (2) |
|
How Big Does the Sample Size Need to Be? Getting the Precision You Want |
|
|
290 | (1) |
|
|
291 | (7) |
|
Falsification and the Logic of Significance Testing |
|
|
292 | (1) |
|
Running a Significance Test |
|
|
292 | (1) |
|
|
293 | (1) |
|
Significance Tests for Simple Regression |
|
|
294 | (2) |
|
Chi-Square Test of Cross-Tabs |
|
|
296 | (1) |
|
|
297 | (1) |
|
Statistical Significance, Practical Significance, and Power |
|
|
298 | (5) |
|
Combinations of Statistical and Practical Significance |
|
|
298 | (2) |
|
Box 9.1 Sources Of Statistical Significance And Of Statistical Insignificance |
|
|
300 | (1) |
|
Failing to Recognize a Difference: Type II Errors |
|
|
301 | (1) |
|
|
301 | (1) |
|
Multiple Comparison Corrections |
|
|
302 | (1) |
|
Sample Size Calculations for Significance Tests |
|
|
302 | (1) |
|
Adjusting Inference for Clustering and Other Complex Sampling |
|
|
303 | (1) |
|
Issues and Extensions of Statistical Inference |
|
|
303 | (2) |
|
Inference With a Nonprobability Sample: What Does It Mean? |
|
|
303 | (1) |
|
Bootstrapping: Inference for Statistics With No Standard Error Formulas |
|
|
304 | (1) |
|
|
305 | (1) |
|
|
305 | (1) |
|
Box 9.2 Tips On Doing Your Own Research: Inferential Statistics |
|
|
306 | (1) |
|
|
306 | (6) |
|
|
306 | (1) |
|
|
307 | (3) |
|
|
310 | (2) |
|
|
312 | (1) |
|
10 Making Sense of Multivariate Statistics |
|
|
313 | (34) |
|
Multiple Regression: The Basics |
|
|
313 | (7) |
|
Box 10.1 How To Run A Multiple Regression Using Software |
|
|
314 | (1) |
|
Multiple Regression for Prediction |
|
|
315 | (1) |
|
Box 10.2 Steps For Predicting With Regression |
|
|
316 | (1) |
|
The Danger (and Necessity) of Out-of-Sample Extrapolation |
|
|
316 | (1) |
|
R-Squared and Adjusted R-Squared |
|
|
316 | (1) |
|
All Else Held Constant: A Bit More Mathematics |
|
|
317 | (1) |
|
|
318 | (1) |
|
Standardized Coefficients: The Relative Importance of Independent Variables |
|
|
319 | (1) |
|
|
320 | (3) |
|
Standard Error of the Coefficient |
|
|
320 | (1) |
|
Confidence Intervals in Regression |
|
|
321 | (1) |
|
Confidence Interval of a Predicted Value |
|
|
321 | (1) |
|
Significance Testing in Regression |
|
|
321 | (1) |
|
Influences on Inference in Multiple Regression |
|
|
322 | (1) |
|
Categorical Independent Variables |
|
|
323 | (4) |
|
Dummy Variables in Regression |
|
|
323 | (1) |
|
Categorical Variables With More Than Two Possible Values |
|
|
324 | (1) |
|
Box 10.3 Representing A Categorical Variable With More Than Two Categories: Diabetes Example |
|
|
324 | (1) |
|
Interpreting the Coefficient of a Dummy Variable |
|
|
325 | (1) |
|
Box 10.4 Interpreting The Coefficient Of A Dummy Variable |
|
|
326 | (1) |
|
Analysis of Variance (ANOVA) |
|
|
327 | (1) |
|
Interactions in Regression |
|
|
327 | (2) |
|
How to Use and Interpret Interaction Variables |
|
|
327 | (2) |
|
Interactions With Quantitative Variables |
|
|
329 | (1) |
|
Always Include Both Main Effects |
|
|
329 | (1) |
|
Functional Form and Transformations in Regression |
|
|
329 | (2) |
|
How to Fit a Curved Relationship |
|
|
330 | (1) |
|
How to Interpret Coefficients When a Variable Is Logged |
|
|
330 | (1) |
|
The Value of Robustness and Transparency |
|
|
331 | (1) |
|
Categorical Variables as Dependent Variables in Regression |
|
|
331 | (2) |
|
|
332 | (1) |
|
Logistic and Probit Regression |
|
|
332 | (1) |
|
What If the Dependent Variable Has More Than Two Categories? |
|
|
333 | (1) |
|
Beware of Unrealistic Underlying Assumptions |
|
|
333 | (1) |
|
Which Statistical Methods Can I Use? |
|
|
333 | (2) |
|
Other Multivariate Methods |
|
|
335 | (7) |
|
|
335 | (1) |
|
|
336 | (1) |
|
Structural Equation Modeling |
|
|
337 | (1) |
|
|
338 | (1) |
|
Time Series and Forecasting |
|
|
339 | (1) |
|
|
340 | (1) |
|
|
340 | (1) |
|
Limited Dependent Variables |
|
|
341 | (1) |
|
|
341 | (1) |
|
More Multivariate Methods Not Covered |
|
|
341 | (1) |
|
|
342 | (1) |
|
Box 10.5 Tips On Doing Your Own Research: Multivariate Statistics |
|
|
342 | (1) |
|
|
343 | (4) |
|
|
343 | (1) |
|
|
343 | (2) |
|
|
345 | (2) |
|
PART IV STRATEGIES FOR CAUSATION |
|
|
347 | (154) |
|
|
348 | (1) |
|
|
349 | (28) |
|
Family Dinners and Teenage Substance Abuse |
|
|
349 | (2) |
|
Correlation Is Not Causation |
|
|
349 | (1) |
|
Box 11.1 Children Who Have Frequent Family Dinners Less Likely To Use Marijuana, Tobacco, And Drink Alcohol |
|
|
350 | (1) |
|
Possible Explanations of a Correlation |
|
|
351 | (4) |
|
Causation and Reverse Causation |
|
|
351 | (1) |
|
|
351 | (1) |
|
|
352 | (2) |
|
Bias From Reverse Causation: Simultaneity Bias |
|
|
354 | (1) |
|
Some More Correlations That Imply Causation |
|
|
354 | (1) |
|
|
355 | (3) |
|
Indirect and Direct Causal Effects |
|
|
356 | (1) |
|
Chance Correlations and Statistical Significance |
|
|
357 | (1) |
|
Arrows, Arrows Everywhere |
|
|
357 | (1) |
|
Why Worry About the Correct Causal Model? |
|
|
358 | (1) |
|
Evidence of Causation: Some Initial Clues |
|
|
358 | (3) |
|
The Cause Happens Before the Effect |
|
|
358 | (1) |
|
The Correlation Appears in Many Different Contexts |
|
|
359 | (1) |
|
Box 11.2 Prominent Epidemiologists Discuss Clues Of Causation |
|
|
359 | (1) |
|
A Plausible Mechanism and Qualitative Evidence |
|
|
359 | (1) |
|
There Are No Plausible Alternative Explanations |
|
|
360 | (1) |
|
Common Causes Are Accounted For in the Analysis |
|
|
361 | (1) |
|
Detective Work and Shoe Leather |
|
|
361 | (1) |
|
Self-Selection and Endogeneity |
|
|
361 | (1) |
|
|
362 | (1) |
|
|
362 | (1) |
|
The Counterfactual Definition of Causation |
|
|
362 | (2) |
|
Box 11.3 Causation And Causality---Two Words For The Same Thing |
|
|
363 | (1) |
|
Box 11.4 Counterfactuals And Potential Outcomes |
|
|
363 | (1) |
|
If We Only Had a Time Machine |
|
|
364 | (1) |
|
Experimentation and Exogeneity: Making Things Happen |
|
|
364 | (7) |
|
Can Exercise Cure Depression? |
|
|
365 | (1) |
|
Why Experimentation Beats Passive Observation |
|
|
365 | (1) |
|
Exogeneity: Intervening in the World |
|
|
366 | (1) |
|
Box 11.5 Exogenous Or Endogenous? It Depends On The Dependent Variable |
|
|
367 | (1) |
|
Box 11.6 The Meaning Of Exogeneity And Endogeneity In Structural Equation Modeling |
|
|
368 | (1) |
|
Control: Holding Things Constant |
|
|
368 | (1) |
|
Experimentation: The Basic Steps |
|
|
369 | (1) |
|
Limited Generalizability of Experiments |
|
|
370 | (1) |
|
Ethical Limitations of Experiments |
|
|
370 | (1) |
|
Experimentation, Policy, and Practice |
|
|
370 | (1) |
|
Conclusion: End of Innocence |
|
|
371 | (1) |
|
Box 11.7 Critical Questions To Ask About Causation |
|
|
371 | (1) |
|
Box 11.8 Tips On Doing Your Own Research: Causation |
|
|
372 | (1) |
|
|
372 | (4) |
|
|
372 | (1) |
|
|
372 | (2) |
|
|
374 | (2) |
|
|
376 | (1) |
|
|
377 | (26) |
|
Private Versus Public Schools |
|
|
377 | (1) |
|
What Is an Observational Study? |
|
|
377 | (2) |
|
The Gold Standard for Description---but Not for Causal Estimation |
|
|
378 | (1) |
|
Limitations of an Observational Study |
|
|
378 | (1) |
|
|
379 | (1) |
|
How Control Variables Help Disentangle a Causal Effect |
|
|
379 | (1) |
|
How to Choose Control Variables |
|
|
379 | (1) |
|
How Did Control Variables Change the Estimate of a Causal Effect? |
|
|
380 | (1) |
|
Matching and Case-Control Studies |
|
|
380 | (3) |
|
|
380 | (2) |
|
|
382 | (1) |
|
Statistical Control: An Empirical Example |
|
|
383 | (8) |
|
Step 1 Speculate on Common Causes |
|
|
384 | (1) |
|
Step 2 Look for Differences |
|
|
385 | (1) |
|
Step 3 Stratify by Control Variables |
|
|
385 | (2) |
|
|
387 | (1) |
|
Box 12.1 Omitted Variables---And The Bias They Cause---By Any Other Name |
|
|
387 | (2) |
|
A Different Choice of Control Variable |
|
|
389 | (1) |
|
Multiple Control Variables |
|
|
389 | (1) |
|
What If the Dependent Variable Is Categorical? Layered Cross-tabs |
|
|
390 | (1) |
|
How to Choose Control Variables |
|
|
391 | (6) |
|
What's Driving the Independent Variable? |
|
|
393 | (1) |
|
Do Not Use Intervening Variables as Controls |
|
|
393 | (1) |
|
Complex Common Causes and Unexplained Correlations |
|
|
394 | (1) |
|
Causes That Can Be Ignored |
|
|
395 | (1) |
|
Choosing Good Control Variables Depends on Your Question |
|
|
395 | (1) |
|
Unmeasured Variables and Omitted Variable Bias |
|
|
396 | (1) |
|
Box 12.2 Jargon: Unmeasured Variables And Unobservables |
|
|
396 | (1) |
|
|
396 | (1) |
|
Conclusion: Observational Studies in Perspective |
|
|
397 | (1) |
|
Box 12.3 Critical Questions To Ask About Observational Studies With Control Variables |
|
|
397 | (1) |
|
Box 12.4 Tips On Doing Your Own Research: Observational Studies With Control Variables |
|
|
398 | (1) |
|
|
398 | (4) |
|
|
398 | (1) |
|
|
399 | (1) |
|
|
400 | (2) |
|
|
402 | (1) |
|
13 Using Regression to Estimate Causal Effects |
|
|
403 | (24) |
|
Cigarette Taxes and Smoking |
|
|
403 | (1) |
|
From Stratification to Multiple Regression |
|
|
403 | (6) |
|
Using More Than One (or Two) Control Variables |
|
|
404 | (1) |
|
Control Variables That Are Quantitative |
|
|
404 | (1) |
|
From Description to Causation: The Education-Earnings Link Reconsidered |
|
|
404 | (2) |
|
Multiple Regression: Brief Overview and Interpretation |
|
|
406 | (1) |
|
How Multiple Regression Is Like Stratification: A Graphical Illustration |
|
|
406 | (2) |
|
Specification: How the Choice of Control Variables Influences Regression Results |
|
|
408 | (1) |
|
What About Unmeasured Variables? |
|
|
409 | (1) |
|
The Effect of Breast-Feeding on Intelligence: Is There a Causal Connection? |
|
|
409 | (6) |
|
Step 1 Speculate on Common Causes |
|
|
410 | (1) |
|
Step 2 Examine the Relationship Between the Independent Variable of Interest and Potential Common Causes |
|
|
410 | (1) |
|
Step 3 Implement Control Variables Through Multiple Regression |
|
|
410 | (3) |
|
How to Interpret Multiple Regression Coefficients: Effects of Controls |
|
|
413 | (1) |
|
How to Interpret Multiple Regression Coefficients: Effect of Interest |
|
|
413 | (1) |
|
Adding and Removing Controls: What Can Be Learned? |
|
|
414 | (1) |
|
|
415 | (1) |
|
Further Topics in Regression for Estimating Causal Effects |
|
|
415 | (3) |
|
Possible Effects of Adding Control Variables |
|
|
416 | (1) |
|
Interactions, Functional Forms, and Categorical Dependent Variables |
|
|
416 | (1) |
|
The Decision to Focus on One Causal Effect---and the Confusion It Can Cause |
|
|
416 | (1) |
|
Box 13.1 When To Call Something A Control Variable |
|
|
417 | (1) |
|
When Is Low R-Squared a Problem? |
|
|
417 | (1) |
|
Software Doesn't Know the Difference, but You Should |
|
|
417 | (1) |
|
Box 13.2 The Health Of Taxi Drivers: Prediction Versus Causation |
|
|
418 | (1) |
|
Multivariate Matching: Using Propensity Scores |
|
|
418 | (2) |
|
Propensity Score Matching |
|
|
419 | (1) |
|
Conclusion: A Widely Used Strategy, With Drawbacks |
|
|
420 | (1) |
|
Box 13.3 Critical Questions To Ask About Studies That Use Regression To Estimate Causal Effects |
|
|
420 | (1) |
|
Box 13.4 Tips On Doing Your Own Research: Multiple Regression To Estimate Causal Effects |
|
|
420 | (1) |
|
|
421 | (5) |
|
|
421 | (1) |
|
|
421 | (3) |
|
|
424 | (2) |
|
|
426 | (1) |
|
14 Randomized Experiments |
|
|
427 | (40) |
|
|
427 | (1) |
|
Florida's Family Transition Program: A Randomized Experiment |
|
|
427 | (1) |
|
Random Assignment: Creating Statistical Equivalence |
|
|
428 | (5) |
|
Random Assignment in Practice |
|
|
429 | (1) |
|
Box 14.1 Manpower Demonstration Research Corporation (Mdrc) |
|
|
429 | (2) |
|
Statistical Equivalence: A Look at the Data |
|
|
431 | (1) |
|
Why Random Assignment Is Better Than Matching or Control Variables |
|
|
432 | (1) |
|
Findings: What Happened in Pensacola |
|
|
432 | (1) |
|
Evidence-Based Public Policies? |
|
|
433 | (1) |
|
Box 14.2 The Coalition For Evidence-Based Policy |
|
|
433 | (1) |
|
The Logic of Randomized Experiments: Exogeneity Revisited |
|
|
433 | (3) |
|
Statistical Significance of an Experimental Result |
|
|
435 | (1) |
|
The Settings of Randomized Experiments |
|
|
436 | (3) |
|
|
436 | (1) |
|
|
436 | (1) |
|
Box 14.3 Practical Difficulties In A Field Experiment About Online Education |
|
|
437 | (1) |
|
Box 14.4 Abduf Latif Jameel Poverty Action Lab At Mit |
|
|
438 | (1) |
|
|
438 | (1) |
|
Generalizability of Randomized Experiments |
|
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439 | (6) |
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Random Assignment Versus Random Sampling |
|
|
439 | (1) |
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The Limited Settings: What Would Happen If Time or Place Were Different? |
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|
440 | (2) |
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Box 14.5 The Rand Health Insurance Experiment |
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442 | (1) |
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Volunteers and Generalizability |
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|
442 | (1) |
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The Ideal Study: Random Sampling, Then Random Assignment |
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443 | (1) |
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Box 14.6 Time-Sharing Experiments For The Social Sciences (Tess) |
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|
444 | (1) |
|
Generalizability of the Treatment |
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444 | (1) |
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Generalizability in the Long Run: Will the Effect Always Be the Same? |
|
|
445 | (1) |
|
Variations on the Design of Experiments |
|
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445 | (4) |
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445 | (2) |
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|
447 | (1) |
|
Levels of a Treatment: Probing a Dose-Response Relationship |
|
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447 | (1) |
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Factors in an Experiment: Probing an Interaction |
|
|
448 | (1) |
|
Within-Subjects (Crossover) Experiments |
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448 | (1) |
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449 | (3) |
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The Hawthorne Effect and the Value of Unobtrusive or Nonreactive Measures |
|
|
449 | (1) |
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Placebo Effect and Blinding |
|
|
450 | (1) |
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Box 14.7 The Perry Preschool Study |
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|
451 | (1) |
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451 | (1) |
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Demoralization and Rivalry |
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|
451 | (1) |
|
|
452 | (1) |
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|
452 | (1) |
|
Analysis of Randomized Experiments |
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452 | (3) |
|
Balancing and the Occasional Need for Control Variables |
|
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453 | (1) |
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Sample Size and Minimal Detectable Effects |
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|
453 | (1) |
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Heterogeneous Treatment Effects |
|
|
453 | (1) |
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454 | (1) |
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Treatment of the Treated in Moving to Opportunity |
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|
454 | (1) |
|
Ethics of Randomized Experiments |
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|
455 | (3) |
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Box 14.8 The Moving To Opportunity Demonstration |
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|
456 | (1) |
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Something for Everyone: The Principle of Beneficence |
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456 | (1) |
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Informed Consent When the Stakes Are High |
|
|
457 | (1) |
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Is Randomization Itself Unethical? |
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|
457 | (1) |
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Qualitative Methods and Randomized Experiments |
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|
458 | (1) |
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Conclusion: A Gold Standard, With Limitations |
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|
458 | (3) |
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Box 14.9 Critical Questions To Ask About A Randomized Experiment |
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|
459 | (1) |
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Box 14.10 Tips On Doing Your Own Research: Randomized Experiments |
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460 | (1) |
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461 | (5) |
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|
461 | (1) |
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|
461 | (3) |
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464 | (2) |
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|
466 | (1) |
|
15 Natural and Quasi Experiments |
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|
467 | (34) |
|
A Casino Benefits the Mental Health of Cherokee Children |
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|
467 | (1) |
|
What Are Natural and Quasi Experiments? |
|
|
467 | (9) |
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Natural Experiments: Finding Exogeneity in the World |
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|
468 | (2) |
|
Quasi Experiments: Evaluating Interventions Without Random Assignment |
|
|
470 | (2) |
|
Why Distinguish Natural Experiments From Quasi Experiments? |
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|
472 | (1) |
|
Box 15.1 Origins Of The Terms Natural Experiment And Quasi Experiment |
|
|
473 | (1) |
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Box 15.2 A Decision Tree For Categorizing Studies |
|
|
473 | (2) |
|
Box 15.3 Oregon'S Health Insurance Lottery |
|
|
475 | (1) |
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Internal Validity of Natural and Quasi Experiments |
|
|
476 | (1) |
|
Exogeneity and Comparability |
|
|
476 | (1) |
|
How Did People Get the Treatment? |
|
|
476 | (1) |
|
|
476 | (1) |
|
Generalizability of Natural and Quasi Experiments |
|
|
477 | (1) |
|
Generalizability of the Treatment Effect |
|
|
477 | (1) |
|
Types of Natural and Quasi Experimental Studies |
|
|
478 | (6) |
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|
478 | (1) |
|
Be Careful Interpreting Significance Tests for Quasi and Natural Experiments |
|
|
479 | (1) |
|
|
479 | (2) |
|
Cross-Sectional Comparisons |
|
|
481 | (2) |
|
Prospective and Retrospective Studies |
|
|
483 | (1) |
|
Box 15.4 Cross-Sectional Analysis Of Longitudinal Data |
|
|
484 | (1) |
|
Difference-in-Differences Strategy |
|
|
484 | (4) |
|
Do Parental Notification Laws Reduce Teenage Abortions and Births? |
|
|
485 | (1) |
|
What Does a Difference-in-Differences Study Assume? |
|
|
486 | (1) |
|
Difference-in-Differences in a Regression Framework |
|
|
487 | (1) |
|
Panel Data for Difference-in-Differences |
|
|
488 | (2) |
|
What Do Panel Difference-in-Differences Studies Assume? |
|
|
489 | (1) |
|
Weaknesses of Panel Difference-in-Differences Studies |
|
|
489 | (1) |
|
Instrumental Variables and Regression Discontinuity |
|
|
490 | (2) |
|
|
490 | (1) |
|
Box 15.5 How To Determine If An Instrument Is Valid |
|
|
491 | (1) |
|
|
492 | (1) |
|
Ethics of Quasi and Natural Experiments |
|
|
492 | (2) |
|
|
494 | (2) |
|
Searching for and Creating Exogeneity |
|
|
494 | (1) |
|
Estimating Causal Effects in Perspective: A Wrap-up to Part IV |
|
|
494 | (1) |
|
Box 15.6 Critical Questions To Ask About Natural And Quasi Experiments |
|
|
495 | (1) |
|
Box 15.7 Tips On Doing Your Own Research: Natural And Quasi Experiments |
|
|
495 | (1) |
|
|
496 | (5) |
|
|
496 | (1) |
|
|
496 | (4) |
|
|
500 | (1) |
|
PART V CONTEXT AND COMMUNICATION |
|
|
501 | (54) |
|
|
502 | (1) |
|
16 The Politics, Production, and Ethics of Research |
|
|
503 | (26) |
|
Risking Your Baby's Health |
|
|
503 | (1) |
|
|
504 | (7) |
|
|
504 | (1) |
|
Box 16.1 The Effects Of Breast-Feeding: Many Studies |
|
|
505 | (1) |
|
|
506 | (1) |
|
Dealing With Uncertainty, Costs, and Benefits |
|
|
507 | (1) |
|
|
507 | (1) |
|
Politics and Other Barriers |
|
|
508 | (2) |
|
A Failure to Move From Research to Policy: The U.S. Poverty Definition |
|
|
510 | (1) |
|
How Can Research Have More Influence? |
|
|
511 | (1) |
|
The Production of Research |
|
|
511 | (6) |
|
|
512 | (1) |
|
How Time and Cost Shape Research |
|
|
513 | (1) |
|
Where Is Research Conducted? |
|
|
513 | (2) |
|
Research Cultures and Disciplines |
|
|
515 | (1) |
|
Which Research Questions Should Be Studied? |
|
|
515 | (2) |
|
|
517 | (8) |
|
The Ethical Review Process |
|
|
517 | (2) |
|
Box 16.2 Template For Informed Consent Form |
|
|
519 | (2) |
|
When You Don't Need an Informed Consent Form |
|
|
521 | (1) |
|
Research Ethics Procedures: It Depends Which Country You're In |
|
|
521 | (1) |
|
How to Keep Data Anonymous or Confidential |
|
|
522 | (1) |
|
Ethical Authorship and Collaboration |
|
|
522 | (1) |
|
Additional Issues in Research Ethics |
|
|
523 | (2) |
|
|
525 | (1) |
|
|
525 | (3) |
|
|
525 | (1) |
|
|
526 | (1) |
|
|
527 | (1) |
|
|
528 | (1) |
|
17 How to Find, Review, and Present Research |
|
|
529 | (26) |
|
|
529 | (5) |
|
|
529 | (2) |
|
Open-Access and e-Journals |
|
|
531 | (1) |
|
|
532 | (1) |
|
Attending Conferences and Seminars |
|
|
532 | (1) |
|
|
533 | (1) |
|
|
533 | (1) |
|
|
533 | (1) |
|
How to Search for Studies |
|
|
534 | (3) |
|
|
534 | (1) |
|
Box 17.1 What Is Google Scholar? |
|
|
534 | (1) |
|
Electronic Resources: Indexes, Full-Text Databases, and Aggregators |
|
|
535 | (1) |
|
|
536 | (1) |
|
Box 17.2 What Is Wikipedia? |
|
|
536 | (1) |
|
Browsing and Following Citation Trails |
|
|
537 | (1) |
|
Bibliographic Citation Software |
|
|
537 | (1) |
|
How to Write a Literature Review |
|
|
537 | (3) |
|
What a Literature Review Should Not Do |
|
|
537 | (1) |
|
What a Literature Review Should Do |
|
|
538 | (1) |
|
Literature Review as a Context for Your Own Study |
|
|
539 | (1) |
|
How to Communicate Your Own Research |
|
|
540 | (10) |
|
The Importance of Rewriting |
|
|
540 | (1) |
|
|
540 | (1) |
|
Organization of a Research Report |
|
|
541 | (2) |
|
|
543 | (2) |
|
|
545 | (1) |
|
Tips for Creating Good Tables |
|
|
545 | (2) |
|
Tips for Creating Good Figures |
|
|
547 | (1) |
|
How to Write About Qualitative Research |
|
|
548 | (1) |
|
Presenting: How It Is and Is Not Like Writing |
|
|
549 | (1) |
|
How to Publish Your Research |
|
|
550 | (1) |
|
|
551 | (1) |
|
|
552 | (3) |
|
|
552 | (1) |
|
|
552 | (1) |
|
|
553 | (2) |
Glossary |
|
555 | (18) |
References |
|
573 | (14) |
Author Index |
|
587 | (8) |
Subject Index |
|
595 | |