Preface |
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xxiii | |
Acknowledgments |
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xxvii | |
About the Authors |
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xxix | |
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1 | (90) |
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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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May the Best Methodology Win |
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4 | (1) |
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Research-Savvy People Rule |
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5 | (1) |
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Research, Policy, and Practice |
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5 | (2) |
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5 | (1) |
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6 | (1) |
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Evidence-Based Policy and Programs |
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6 | (1) |
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7 | (1) |
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7 | (1) |
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7 | (1) |
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8 | (1) |
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8 | (4) |
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Secondary and Primary Research |
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8 | (1) |
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It Comes in Various Shapes and Sizes |
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9 | (1) |
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9 | (1) |
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It's Uncertain and Contingent |
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10 | (1) |
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10 | (1) |
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Bits and Pieces of a Puzzle |
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10 | (2) |
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It Involves Competition and Criticism |
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12 | (1) |
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It Can Be Quantitative, Qualitative, or a Mix of Both |
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12 | (1) |
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Formulating Research Questions |
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12 | (2) |
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How the World is---Not How It Should Be |
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12 | (1) |
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Applied and Basic Research |
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12 | (1) |
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Questions We Ideally Would Like to Answer, and Those We Really Can |
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13 | (1) |
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Descriptive and Causal Research |
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14 | (2) |
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Description: What is the World Like? |
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14 | (1) |
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Causation: How Would the World Be Different If Something Changed? |
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15 | (1) |
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Causal Research Needs Qualitative Research |
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15 | (1) |
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Don't Confuse Correlation With Causation |
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16 | (1) |
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Epistemology: Ways of Knowing |
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16 | (3) |
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17 | (1) |
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17 | (1) |
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Proof Requires Fresh Data |
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18 | (1) |
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Truth in Social Science: Controversy and Consensus |
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19 | (1) |
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Approaching Research From Different Angles |
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19 | (2) |
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20 | (1) |
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20 | (1) |
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21 | (1) |
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21 | (1) |
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Conclusion: The Road Ahead |
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22 | (3) |
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25 | (30) |
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Fighting Crime in New York City |
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25 | (1) |
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26 | (3) |
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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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27 | (1) |
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Theories Take Different Forms in Different Disciplines |
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28 | (1) |
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Where Do Theories Come From? |
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29 | (1) |
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29 | (1) |
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Theories, Norms, and Values |
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29 | (1) |
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Modifiable and Nonmodifiable Variables |
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30 | (1) |
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30 | (7) |
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Variables and Relationships |
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31 | (1) |
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Independent and Dependent Variables |
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31 | (1) |
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32 | (1) |
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Direction of a Relationship |
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33 | (2) |
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35 | (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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36 | (1) |
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37 | (1) |
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Same Theory, Different Unit of Analysis |
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38 | (1) |
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38 | (6) |
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Do Smaller Classes Help Kids Learn? |
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41 | (1) |
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42 | (1) |
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43 | (1) |
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Usefulness of a Logic Model |
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44 | (1) |
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Tips for Creating a Logic Model |
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45 | (3) |
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Additional Issues in Theory Building |
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48 | (2) |
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Theories of the Independent Variable |
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48 | (1) |
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48 | (1) |
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The Aggregation Problem and the Ecological Fallacy |
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49 | (1) |
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Hierarchical (Multilevel) Models and Contextual Variables |
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50 | (1) |
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50 | (1) |
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Conclusion: Theories Are Practical |
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50 | (5) |
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55 | (36) |
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Fighting Malaria in Kenya |
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55 | (2) |
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Theory, Causes, and Qualitative Research |
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56 | (1) |
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What is Qualitative Research? |
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57 | (4) |
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Contrasting Qualitative With Quantative Research |
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57 | (1) |
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Small-n Studies and Purposive Sampling |
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58 | (1) |
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Focus on Cases Rather Than Variables |
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59 | (1) |
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Advantages of Qualitative Research |
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59 | (1) |
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Schools of Thought in Qualitative Research |
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60 | (1) |
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Existing Qualitative Data |
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61 | (1) |
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Archival and Other Written Documents |
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62 | (1) |
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Visual Media, Popular Culture, and the Internet |
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62 | (1) |
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62 | (5) |
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63 | (1) |
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Semistructured Interviews |
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63 | (2) |
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Asking Truly Open-Ended Questions |
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65 | (1) |
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65 | (1) |
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Some Practical Considerations When Doing Interviews |
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66 | (1) |
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67 | (4) |
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What Do People Think of Congestion Pricing? |
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67 | (1) |
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67 | (3) |
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Why a Focus Group? Why Not Individual Interviews? |
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70 | (1) |
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Telephone and Online Focus Groups |
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70 | (1) |
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71 | (1) |
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Participant Observation and Ethnography |
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71 | (2) |
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Why Do the Homeless Refuse Help? |
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71 | (1) |
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Levels on a Participation-Observation Continuum |
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72 | (1) |
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Secret Shopping and Audit Studies |
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73 | (1) |
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73 | (2) |
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Maryland's Gun Violence Act |
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74 | (1) |
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Selecting a Case to Study |
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75 | (1) |
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Qualitative Data Analysis |
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75 | (5) |
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Integration of Analysis and Data Gathering |
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75 | (1) |
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Coding and Content Analysis |
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76 | (2) |
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Qualitative Data Analysis Software |
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78 | (2) |
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The Qualitative-Quantitative Debate |
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80 | (5) |
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A Brief History of the Debate |
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80 | (1) |
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Blurring the Lines: How Qualitative and Quantitative Approaches Overlap |
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81 | (1) |
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A Qualitative-Quantitative Research Cycle |
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82 | (2) |
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Mixed-Methods Research and Triangulation |
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84 | (1) |
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Ethics in Qualitative Research |
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85 | (1) |
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Presenting Qualitative Data |
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85 | (1) |
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Uncovering Sensitive Information |
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85 | (1) |
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Deception in Participant Observation |
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86 | (1) |
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Should Qualitative Research Empower People? |
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86 | (1) |
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Conclusion: Matching Methods to Questions |
|
|
86 | (5) |
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PART II: STRATEGIES FOR DESCRIPTION |
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|
91 | (236) |
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93 | (46) |
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93 | (1) |
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93 | (2) |
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Measurement in Qualitative Research |
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94 | (1) |
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94 | (1) |
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Measurement: The Basic Model and a Road Map |
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95 | (1) |
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95 | (4) |
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Defining Can Be Difficult |
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96 | (1) |
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Where Do Conceptualizations Come From? |
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97 | (1) |
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Manifest and Latent Constructs |
|
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98 | (1) |
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98 | (1) |
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99 | (7) |
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Birth of the U. S. Poverty Measure |
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99 | (2) |
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101 | (1) |
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102 | (1) |
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102 | (1) |
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103 | (3) |
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106 | (2) |
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Is the U. S. Poverty Measure Valid? |
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106 | (1) |
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106 | (1) |
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107 | (1) |
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108 | (1) |
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Criterion-Related Validity |
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108 | (7) |
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Self-Reported Drug Use: Is It Valid? |
|
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108 | (2) |
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Does the Measure Predict Behavior? |
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110 | (3) |
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Limitations of Validity Studies |
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113 | (2) |
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115 | (3) |
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115 | (1) |
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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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Error Model of Measurement |
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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 | (3) |
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Validity and Reliability in Qualitative Research |
|
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124 | (1) |
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124 | (8) |
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125 | (2) |
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127 | (1) |
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Turning Categorical Variables into Quantitative Ones |
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128 | (3) |
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Units of Analysis and Levels of Measurement |
|
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131 | (1) |
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Measurement in the Real World: Trade-Offs and Choices |
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132 | (7) |
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132 | (1) |
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133 | (1) |
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How Will it Affect the Quality and Rate of Responding? |
|
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133 | (1) |
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Validity-Reliablity Trade-Off |
|
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133 | (1) |
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Use an Established Measure or Invent a New One? |
|
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134 | (1) |
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135 | (4) |
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139 | (42) |
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Gauging the Fallout From Hurricane Katrina |
|
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139 | (1) |
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140 | (5) |
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Population of Interest, Sampling, and Generalizability |
|
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141 | (1) |
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Are Experiments More Generalizable? |
|
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141 | (1) |
|
Replicating Research and Meta-Analysis |
|
|
142 | (1) |
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Are Relationships More Generalizable? Health and Happiness in Moldova |
|
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143 | (1) |
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Generalizability of Qualitative Studies |
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144 | (1) |
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145 | (3) |
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Population, Sample, and Inference |
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145 | (1) |
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146 | (2) |
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Coverage and Nonresponse Bias |
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148 | (5) |
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Sampling Frames and Coverage Issues |
|
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148 | (1) |
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148 | (1) |
|
When Does Nonresponse Cause Bias? |
|
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149 | (2) |
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When Do Coverage Problems Cause Bias? |
|
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151 | (1) |
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152 | (1) |
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153 | (4) |
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153 | (1) |
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154 | (1) |
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Sampling Online: Open Web Polls and Internet Access Panels |
|
|
154 | (2) |
|
Purposive Sampling and Qualitative Research |
|
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156 | (1) |
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Random (Probability) Sampling |
|
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157 | (3) |
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The Contribution of Random Sampling |
|
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157 | (1) |
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Random Sampling Versus Randomized Experiments |
|
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158 | (1) |
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158 | (2) |
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Sampling Distributions and Statistical Inference |
|
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160 | (2) |
|
Confidence Intervals (Margins of Error) |
|
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162 | (7) |
|
Calculating a Confidence Interval or Margin of Error |
|
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163 | (1) |
|
Interpreting Confidence Intervals (Margins of Error) |
|
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163 | (2) |
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Sample Size and Sampling Precision |
|
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165 | (1) |
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Variability and Sampling Precision |
|
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166 | (1) |
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What a Margin of Error Does Not Tell You |
|
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167 | (1) |
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Two Meanings of the Word Sample |
|
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168 | (1) |
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169 | (6) |
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169 | (1) |
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170 | (1) |
|
Disproportionate Sampling (Oversampling) |
|
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170 | (1) |
|
Poststratification Weighting |
|
|
171 | (1) |
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Sampling With Probabilities Proportional to Size (PPS) |
|
|
172 | (1) |
|
Multistage and Cluster Sampling |
|
|
172 | (2) |
|
Design Effects: Complex Survey Sampling Corrections |
|
|
174 | (1) |
|
Random Digit Dialing Sampling |
|
|
174 | (1) |
|
Sampling and Generalizability: A Summary |
|
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175 | (6) |
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181 | (30) |
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181 | (1) |
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What Are Quantitative Data? |
|
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181 | (2) |
|
Quantitative Data Versus Quanlitative Variables |
|
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182 | (1) |
|
Quantitative Versus Qualitative Research |
|
|
182 | (1) |
|
Forms of Quantitative Data |
|
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183 | (4) |
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Micro, Aggregate, and Multileval Data |
|
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183 | (3) |
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186 | (1) |
|
Where Do Quantitative Data Come From? |
|
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187 | (1) |
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187 | (5) |
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Adapting Administrative Data for Research |
|
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188 | (2) |
|
Vital Statistics, Crime Reports, and Unemployment Claims |
|
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190 | (1) |
|
Ethics of Administrative Record Data |
|
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191 | (1) |
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192 | (3) |
|
Where to Find Published Tables |
|
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192 | (1) |
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Published Time-Series and Panel Data |
|
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192 | (3) |
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195 | (11) |
|
Secondary Analysis of Public Use Data: A New Model of Research? |
|
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195 | (1) |
|
Know the Major Surveys in Your Field |
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195 | (9) |
|
Accessing and Analyzing Public Use Data |
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204 | (1) |
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204 | (1) |
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Ethics of Public Use Microdata |
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205 | (1) |
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206 | (1) |
|
Some Limitations of Secondary Data |
|
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206 | (1) |
|
Does Data Availability Distort Research? |
|
|
206 | (1) |
|
When to Collect Original Data? |
|
|
207 | (1) |
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|
207 | (4) |
|
Primary Data Collection: Surveys and Observation |
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211 | (30) |
|
Taking the Nation's Economic Pulse |
|
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211 | (1) |
|
When Should You Do a Survey? |
|
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212 | (1) |
|
Do You Know Enough About the Topic? |
|
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212 | (1) |
|
Does the Information Exist Already in Another Source? |
|
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212 | (1) |
|
Can People Tell You What You Want to know? |
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212 | (1) |
|
Will People Provide Truthful Answers? |
|
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213 | (1) |
|
Steps in the Survey Research Process |
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213 | (3) |
|
Identify the Population and Sampling Strategy |
|
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213 | (1) |
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214 | (1) |
|
Pretest Questionnaire and Survey Procedures |
|
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214 | (1) |
|
Recruit and Train Interviewers |
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215 | (1) |
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215 | (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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216 | (1) |
|
Modes of Survey Data Collection |
|
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216 | (8) |
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Intercept Interview Surveys |
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216 | (1) |
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Household Interview Surveys |
|
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217 | (1) |
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Telephone Interview Surveys |
|
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218 | (1) |
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Mail Self-Administered Surveys |
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219 | (2) |
|
Group Self-Adminstered Surveys |
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221 | (1) |
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221 | (2) |
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Establishment (Business or Organization) Surveys |
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223 | (1) |
|
Panel or Longitudinal Surveys |
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224 | (1) |
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224 | (8) |
|
Develop an Outline of Survey Items |
|
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224 | (1) |
|
If You Could Ask Only One or Two Questions |
|
|
224 | (1) |
|
Prepare Mock Tables and Charts of Survey Results |
|
|
225 | (1) |
|
Look for Prior Surveys on Your Topic |
|
|
225 | (1) |
|
Hook Respondents With Your First Few Questions |
|
|
225 | (2) |
|
Closed-Ended Versus Open-Ended Questions |
|
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227 | (1) |
|
Some Advice On Question Wording |
|
|
228 | (4) |
|
Put Yourself in Your Respondent's Shoes |
|
|
232 | (1) |
|
Ethics of Survey Research |
|
|
232 | (2) |
|
|
232 | (1) |
|
Pushing for a High Response Rate |
|
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232 | (1) |
|
Overburdening Respondents |
|
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233 | (1) |
|
Protecting privacy and Confidentiality |
|
|
233 | (1) |
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233 | (1) |
|
Making Survey Data Available for Public Use |
|
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234 | (1) |
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|
234 | (3) |
|
Observing Social Disorder |
|
|
234 | (3) |
|
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237 | (4) |
|
Making Sense of the Numbers |
|
|
241 | (52) |
|
``Last Weekend I Walked Eight'' |
|
|
241 | (1) |
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|
242 | (5) |
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|
242 | (1) |
|
Rates or Why Counts Often Mislead |
|
|
243 | (1) |
|
Percent Change and Percentage Point Change |
|
|
244 | (1) |
|
The Strangeness of Percent Change on the Return Trip |
|
|
245 | (1) |
|
Rates of Change and Rates of Change of Rates |
|
|
245 | (1) |
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|
246 | (1) |
|
|
246 | (1) |
|
|
247 | (3) |
|
Distribution of a Categorical Variable |
|
|
247 | (1) |
|
Distribution of a Quantitative Variable |
|
|
248 | (2) |
|
Measures of Center: Mean and Median |
|
|
250 | (2) |
|
When to Use Median? When to Use Mean? |
|
|
251 | (1) |
|
Measures of Spread and Variation |
|
|
252 | (4) |
|
|
253 | (1) |
|
Pay Attention to the Standard Deviation, Not Just the Mean |
|
|
253 | (1) |
|
|
254 | (1) |
|
Quantiles: Another Way to Measure Spread |
|
|
255 | (1) |
|
Conefficient of Variation: A Way to Compare Spread |
|
|
255 | (1) |
|
Relationships Between Categorical Variables |
|
|
256 | (4) |
|
|
256 | (2) |
|
Relative Risks and Odds Ratios: Another Way to Show Relationships in Categorical Data |
|
|
258 | (1) |
|
Adjusted and Standardized Rates: When to Use Them |
|
|
259 | (1) |
|
Relationships Between Quantitative Variables: Scatterplots and Correlation |
|
|
260 | (2) |
|
|
260 | (1) |
|
|
261 | (1) |
|
Simple Regression: Best-Fit Straight Line |
|
|
262 | (6) |
|
Interpreting the Regression Coefficient (Slope) |
|
|
264 | (2) |
|
Can a Regression Coefficient Be Interpreted as a Causal Effect? |
|
|
266 | (1) |
|
|
267 | (1) |
|
R-Squared and Residuals: How Well Does the Line Fit the Data? |
|
|
267 | (1) |
|
Effect Size and Practical Significance |
|
|
268 | (1) |
|
|
268 | (1) |
|
|
268 | (1) |
|
Inference and the Standard Error |
|
|
269 | (1) |
|
|
270 | (2) |
|
Univariate Statistics and Relationships Both Have Confidence Intervals |
|
|
271 | (1) |
|
Confidence Intervals Only Reflect Some Sources of Error |
|
|
271 | (1) |
|
|
272 | (4) |
|
Falsification and the Logic of Significance Testing |
|
|
272 | (1) |
|
Running a Significance Test |
|
|
273 | (1) |
|
|
274 | (1) |
|
Chi-Square Test of Cross-Tabs |
|
|
275 | (1) |
|
|
275 | (1) |
|
Universality of the p Value |
|
|
275 | (1) |
|
Statistical Significance, Practical Significance, and Power |
|
|
276 | (7) |
|
Combinations of Statistical and Practical Significance |
|
|
276 | (3) |
|
Failing to Recognize a Difference: Type II Errors |
|
|
279 | (1) |
|
|
280 | (1) |
|
Multiple Comparison Corrections |
|
|
281 | (1) |
|
The Debate About Significance Testing |
|
|
281 | (1) |
|
Sample Size Calculations: Getting the Precision You Want |
|
|
281 | (1) |
|
Adjusting Inference for Clustering and Other Complex Sampling |
|
|
282 | (1) |
|
|
283 | (1) |
|
|
283 | (1) |
|
Statistical Packages: SAS, IBM® SPSS®, and Stata |
|
|
283 | (1) |
|
Specialzed Modeling and Matrix Language Programs |
|
|
283 | (1) |
|
Conclusion: Tools for Description and Causation |
|
|
283 | (10) |
|
Making Sense of Multivariate Statistics |
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293 | (34) |
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Multiple Regression: The Basics |
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293 | (6) |
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Multiple Regression for Prediction |
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295 | (1) |
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The Danger (and Necessity) of Out-of-Sample Extrapolation |
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295 | (1) |
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R-Squared and Adjusted R-Squared |
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296 | (1) |
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All Else Held Constant: A Bit More Mathematics |
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296 | (1) |
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297 | (1) |
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When You Can't Disentangle the Independent Variables |
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297 | (1) |
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How Many Independent Variables Can One Regression Have? |
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298 | (1) |
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Standardized Coefficients: The Relative Importance of Independent Variables |
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299 | (1) |
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299 | (4) |
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Standard Error of the Coefficient |
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299 | (1) |
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Confidence Intervals in Regression |
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300 | (1) |
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Confidence Interval of a Predicted Value |
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301 | (1) |
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Significance Testing in Regression |
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301 | (1) |
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Influences on Inference in Multiple Regression |
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302 | (1) |
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Categorical Independent Variables |
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303 | (4) |
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303 | (1) |
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Isn't There a Simpler Way to Estimate Differences in Means? |
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303 | (1) |
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Categorical Varibles With More Than Two Possible Values |
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304 | (1) |
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Interpreting the Coefficient of a Dummy Variable |
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305 | (2) |
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Adjusting Rates and Other Varibles |
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307 | (1) |
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Analysis of Variance (ANOVA) |
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307 | (1) |
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Interactions in Regression |
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307 | (3) |
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How to Use and Interpret Interaction Variables |
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308 | (2) |
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Interactions with Quantitative Variables |
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310 | (1) |
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Always Include Both Main Effects |
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310 | (1) |
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Functional Form and Transformations in Regression |
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310 | (3) |
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How to Fit a Curved Relationship |
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311 | (1) |
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How to Interpret Coefficients When a Variable is Logged |
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311 | (1) |
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The Value of Robustness and Transparency |
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312 | (1) |
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Categorical Variables as Dependent Variables in Regression |
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313 | (2) |
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313 | (1) |
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Logistic and Probit Regression |
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314 | (1) |
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314 | (1) |
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What if the Dependent Variable Has More Than Two Categories? |
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314 | (1) |
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Beware of Unrealistic Underlying Assumptions |
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315 | (1) |
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Which Statistical Methods Can I Use? |
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315 | (2) |
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Other Multivariate Methods |
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317 | (8) |
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317 | (1) |
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318 | (2) |
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Structural Equation Modeling |
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320 | (1) |
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320 | (2) |
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Time Series and Forecasting |
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322 | (1) |
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323 | (1) |
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324 | (1) |
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Limited Dependent Variables |
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324 | (1) |
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325 | (1) |
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More Multivariate Methods Not Covered |
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325 | (1) |
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325 | (2) |
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PART III: STRATEGIES FOR CAUSATION |
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327 | (138) |
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329 | (26) |
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Family Dinners and Teenage Substance Abuse |
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329 | (2) |
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Correlation Is Not Causation |
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331 | (1) |
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Possible Explanations of a Correlation |
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331 | (5) |
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Causation and Reverse Causation |
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331 | (1) |
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332 | (1) |
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332 | (2) |
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Bias From an Unknown or Complex Common Cause |
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334 | (1) |
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Bias From Reverse Causation: Simultaneity Bias |
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335 | (1) |
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Other Examples of Correlation That Imply Causation |
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335 | (1) |
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336 | (3) |
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Chance Correlations and Statistical Significance |
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337 | (1) |
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Arrows, Arrows Everywhere |
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338 | (1) |
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Why Worry About the Correct Causal Model? |
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339 | (1) |
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Evidence of Causation: Some Initial Clues |
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339 | (4) |
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The Cause Happens Before the Effect |
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340 | (1) |
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The Correlation Appears in Many Different Contexts |
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340 | (1) |
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A Plusible Mechanism and Qualitative Evidence |
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341 | (1) |
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There Are No Plausible Alternative Explanations |
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341 | (1) |
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Common Causes Are Accounted for in the Analysis |
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342 | (1) |
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Self-Selection and Endogeneity |
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343 | (2) |
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343 | (1) |
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344 | (1) |
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The Counterfactual Definition of Causation |
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345 | (1) |
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If We Only Had a Time Machine |
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346 | (1) |
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Experimentation and Exogeneity: Making Things Happen |
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346 | (6) |
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Can Exercise Cure Depression? |
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347 | (1) |
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Why Experimentation Beats Passive Observation |
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347 | (1) |
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Exogeneity: Imposing a Change |
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348 | (1) |
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Control: Holding Things Constant |
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349 | (1) |
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Experimentation: A Review of the Basic Steps |
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350 | (1) |
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350 | (1) |
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Limited Generalizability of Lab Experiments |
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351 | (1) |
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Ethical Difficulties Are Inherent in Experimentation |
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351 | (1) |
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Experimentation, Policy, and Practice |
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351 | (1) |
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Conclusion: End of Innocence |
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352 | (3) |
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Observational Studies With Control Variables |
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355 | (40) |
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Private Versus Public Schools |
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355 | (1) |
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355 | (2) |
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The Gold Standard for Description---but Not for Causal Estimation |
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356 | (1) |
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Limitations of an Observational Study |
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357 | (1) |
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357 | (2) |
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How Control Variables Help Disentangle a Causal Effect |
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358 | (1) |
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How to Choose Control Variables |
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358 | (1) |
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How Did Control Variables Change the Estimate of a Causal Effect? |
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|
359 | (1) |
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An Empirical Example: Education and Earnings |
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359 | (7) |
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Speculate on Common Causes |
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360 | (1) |
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361 | (1) |
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Stratify by Control Variables |
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361 | (1) |
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How Does Controlling for Aptitude Change the Estimate of the Effect of College? |
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362 | (1) |
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363 | (1) |
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364 | (1) |
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A Different Choice of Control Variable |
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364 | (1) |
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More Than One Control Variable at a Time |
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365 | (1) |
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How to Choose Control Variables |
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366 | (6) |
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The Importance of Using Path Diagrams |
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367 | (1) |
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Intervening Variables Should Not Be Used as Controls |
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368 | (1) |
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Complex Common Causes and Unexplained Correlations |
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369 | (1) |
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Causes That Can Be Ignored |
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|
369 | (1) |
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Choosing Good Control Variables Depends on Your Question |
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|
370 | (1) |
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Unmeasured Variables and Omitted Variables Bias |
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370 | (1) |
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|
371 | (1) |
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|
372 | (1) |
|
From Stratification to Multiple Regression |
|
|
372 | (7) |
|
Using More Than One (Or Two) Control Variables |
|
|
372 | (1) |
|
Control Variables That Are Quantitative |
|
|
372 | (1) |
|
Regression: From Description to Causation |
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|
373 | (1) |
|
Multiple Regression: Brief Overview and Interpretation |
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|
374 | (2) |
|
How Multiple Regression Is Like Stratification: A Graphical Illustration |
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|
376 | (1) |
|
Specification: How the Choice of Control Variables Influences Regression Results |
|
|
377 | (2) |
|
What About Unmeasured Variables? |
|
|
379 | (1) |
|
The Effect of Breastfeeding on Intelligence: Is There a Causal Connection? |
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|
379 | (7) |
|
|
379 | (1) |
|
Speculate on Common Causes |
|
|
379 | (1) |
|
Examine the Relationship Between the Independent Variable of Interest and Potential Common Causes |
|
|
380 | (1) |
|
Implement Control Variables Throguh Multiple Regression |
|
|
380 | (2) |
|
How to Interpret Multiple Regression Coefficients: Effect of Controls |
|
|
382 | (1) |
|
How to Interpret Multiple Regression Coefficents: Effect of Interest |
|
|
382 | (2) |
|
Adding and Removing Controls: What Can Be Learned? |
|
|
384 | (2) |
|
|
386 | (1) |
|
Further Topics in Multiple Regression |
|
|
386 | (4) |
|
Possible Effects of Adding Control Variables |
|
|
386 | (1) |
|
Interactions, Functional Form, and Categorical Dependent Variables |
|
|
386 | (1) |
|
The Decision to Focus on One Causal Effect---and the Confusion It Can Cause |
|
|
387 | (1) |
|
When Is Low R-Squared a Problem? |
|
|
388 | (2) |
|
Software Doesn't Know the Difference, but You Should |
|
|
390 | (1) |
|
Control Varibles in Perspective |
|
|
390 | (5) |
|
Randomized Field Experiments |
|
|
395 | (32) |
|
|
395 | (1) |
|
Florida's Family Transition Program: A Randomized Field Experiment |
|
|
396 | (1) |
|
Random Assignment: Creating Statistical Equivalence |
|
|
397 | (5) |
|
Random Assignment in Practice |
|
|
397 | (2) |
|
Statistical Equivalence: A Look at the Data |
|
|
399 | (1) |
|
Why Random Assignment Is Better Than Matching or Control Varibles |
|
|
400 | (2) |
|
Findings: What Happened in Pensacola |
|
|
402 | (1) |
|
The Logic of Randomized Experiments: Another Look |
|
|
402 | (3) |
|
Statistical Significance of an Experimental Result |
|
|
404 | (1) |
|
Generalizability of Randomized Experiments |
|
|
405 | (6) |
|
Random Assignment Versus Random Sampling |
|
|
405 | (1) |
|
The Limited Settings of Randomized Field Experiments |
|
|
406 | (2) |
|
Volunteers and Generalizability |
|
|
408 | (1) |
|
The Ideal Study: Random Sampling, Then Random Assignment |
|
|
409 | (2) |
|
Generalizability of the Treatment |
|
|
411 | (1) |
|
Variations on the Design of Experiments |
|
|
411 | (2) |
|
|
411 | (1) |
|
|
412 | (1) |
|
Heterogeneous Treatment Effects |
|
|
412 | (1) |
|
Human Artifacts in Experiments |
|
|
413 | (4) |
|
Placebo Effect and Blinding |
|
|
413 | (1) |
|
Unobtrusive or Nonreactive Measures |
|
|
414 | (1) |
|
|
415 | (1) |
|
|
415 | (1) |
|
Demoralization and Rivalry |
|
|
416 | (1) |
|
|
417 | (1) |
|
|
417 | (1) |
|
Analysis of Randomized Experiments |
|
|
417 | (4) |
|
Balancing and the Occasional Need for Control Variables |
|
|
418 | (1) |
|
Sample Size and Minimal Detectable Effects |
|
|
418 | (1) |
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|
418 | (1) |
|
Treatment of the Treated in Moving to opportunity |
|
|
419 | (2) |
|
Qualitative Methods and Experiments |
|
|
421 | (1) |
|
|
422 | (5) |
|
Natural and Quasi Experiments |
|
|
427 | (38) |
|
A Casino Benefits the Mental Health of Cherokee Children |
|
|
427 | (1) |
|
What Are Natural and Quasi Experiments? |
|
|
428 | (8) |
|
Natural Experiments: Taking Advantage of Exogenous Events |
|
|
428 | (2) |
|
Quasi Experiments: Evaluating Intentional or Planned Treatments |
|
|
430 | (2) |
|
Why Distinguish Quasi Experiments From Natural Experiments? |
|
|
432 | (4) |
|
Internal Validity of Natural and Quasi Experiments |
|
|
436 | (1) |
|
Exogeneity and Comparability |
|
|
436 | (1) |
|
Theory of the Independent Variable |
|
|
437 | (1) |
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|
437 | (1) |
|
Generalizability of Natural and Quasi Experiments |
|
|
437 | (1) |
|
Generalizability of the Treatment Effect |
|
|
438 | (1) |
|
Types of Natural and Quasi Experimental Studies |
|
|
438 | (13) |
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|
439 | (1) |
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|
440 | (2) |
|
Cross-Sectional Comparisons |
|
|
442 | (2) |
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|
444 | (3) |
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|
447 | (2) |
|
Prospective and Retrospective Studies |
|
|
449 | (2) |
|
Difference-in-Differences Strategy |
|
|
451 | (4) |
|
Do Parental Notification Laws Reduce Teenage Abortions and Births? |
|
|
451 | (1) |
|
What Does a Difference-in-Differences Study Assume? |
|
|
452 | (2) |
|
Retrospective Pretests and Other Retrospective Variables |
|
|
454 | (1) |
|
Difference-in-Differences in a Regression Framework |
|
|
455 | (1) |
|
Panel Data for Difference in Differences |
|
|
455 | (3) |
|
What Do Panel Difference-in-Differences Studies Assume? |
|
|
456 | (1) |
|
Weaknesses of Panel Difference-in-Differeces Studies |
|
|
457 | (1) |
|
Instrumental Variables and Regression Discontinuity |
|
|
458 | (3) |
|
|
458 | (1) |
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|
459 | (2) |
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|
461 | (4) |
|
Searching for and Creating Exogeneity |
|
|
461 | (1) |
|
Estimating Causal Effects in Perspective: A Wrap-Up to Part III |
|
|
461 | (4) |
|
|
465 | (52) |
|
The Politics, Production, and Ethics of Research |
|
|
467 | (22) |
|
Risking Your Baby's Health |
|
|
467 | (1) |
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|
468 | (9) |
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|
468 | (4) |
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|
472 | (2) |
|
Politics and Other Barriers |
|
|
474 | (2) |
|
How Can Research Have More Influence? |
|
|
476 | (1) |
|
The Production of Research |
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|
477 | (4) |
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|
477 | (1) |
|
How Time and Cost Shape Research |
|
|
478 | (1) |
|
Where is Research Conducted? |
|
|
479 | (2) |
|
Research Cultures and Disciplines |
|
|
481 | (1) |
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|
481 | (5) |
|
Poisoned by New York's Best Restaurants |
|
|
482 | (1) |
|
History of Human Subjects Abuses in Research |
|
|
482 | (1) |
|
Principles of Ethical Research Emerge |
|
|
482 | (1) |
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|
483 | (1) |
|
Ethical Dilemmas in Research |
|
|
484 | (1) |
|
That Ethical State of Mind |
|
|
485 | (1) |
|
|
486 | (3) |
|
How to Find, Focus, and Present Research |
|
|
489 | (28) |
|
|
489 | (4) |
|
|
489 | (3) |
|
Open-Access and e-Journals |
|
|
492 | (1) |
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|
492 | (1) |
|
Attending Conferences and Seminars |
|
|
492 | (1) |
|
|
493 | (1) |
|
|
493 | (1) |
|
How to Search for Studies |
|
|
493 | (5) |
|
|
494 | (1) |
|
Electronic Resources: Indexes, Full-Text Databases, and Aggregators |
|
|
495 | (1) |
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|
496 | (1) |
|
Browsing and Following Citation Trails |
|
|
497 | (1) |
|
Bibliographic Citation Software |
|
|
498 | (1) |
|
How to Focus Your Own Research Question |
|
|
498 | (5) |
|
Different Kinds of Researchers |
|
|
498 | (1) |
|
For Those Getting Started: Topics, Questions, and Problems |
|
|
498 | (1) |
|
Make Your Question Postitive, Not Normative |
|
|
499 | (1) |
|
Know If Your Question is Descriptive or Causal |
|
|
500 | (1) |
|
Distinguish the Question You Want to Answer From the Question You Can Answer |
|
|
500 | (1) |
|
For the Applied Researcher Given a Policy or Practice Question to Answer |
|
|
501 | (1) |
|
For Experienced Researchers: Finding an Important (but Doable) Question |
|
|
502 | (1) |
|
How to Write and Present Research |
|
|
503 | (12) |
|
The Importance of Rewriting |
|
|
503 | (1) |
|
|
503 | (1) |
|
Organization of a Research Report |
|
|
504 | (3) |
|
|
507 | (2) |
|
|
509 | (1) |
|
Tips for Creating Good Tables |
|
|
509 | (2) |
|
Tips for Creating Good Figures |
|
|
511 | (1) |
|
How to Write About Qualitative Research |
|
|
511 | (3) |
|
Presenting: How it is and is Not Like Writing |
|
|
514 | (1) |
|
|
515 | (2) |
Glossary |
|
517 | (20) |
References |
|
537 | (12) |
Index |
|
549 | |