Experimental designs:
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne
Sage
[2021]
|
| Schriftenreihe: | The Sage quantitative research kit
6th volume |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Enthält Literaturverzeichnis Seite 169-218 und Index |
| Beschreibung: | xii, 224 Seiten Diagramme |
| ISBN: | 9781526426628 |
Internformat
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Datensatz im Suchindex
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| adam_text | CONTENTS List of Figures, Tables and Boxes About the Authors 1 2 Introduction xi xiii 1 Contextualising Randomised Experiments in a Wide Range of Causal Designs Causal Designs and the Scientific Meaning of Causality Why Should Governments and Agencies Care About Causal Designs? 7 9 11 R is for Random 15 Comparisons in Science Counterfactuals Randomisation Procedures for Random Assignment (How to Randomise) Simple Random Assignment Alternatives to Simple Random Assignment: Restrictive Allocation The Randomised Block Design Trickle Flow Random Assignment Matched Pairs Design Minimisation Randomisation in Practice: The Randomiser Units of Randomisation (What to Randomise?) Person-Based Randomisation Place-Based Randomisation Temporal-Based Randomisation A Final Word Regarding the Choice of Units of Randomisation Should We Use Significance Tests for Baseline Imbalances After Randomisation? Inferential Statistics and Probability Theory Randomisation and Sample Size Considerations Summarising the Benefits of Randomisation 16 17 20 22 23 25 26 29 31 35 36 36 37 39 41 42 44 46 48 50
viil 3 EXPERIMENTAL DESIGNS C is for Control 53 What Do We Mean by Control? 54 Threats to Internal Validity 54 History Maturation 58 60 Testing Instrumentation 61 63 Statistical Regression to the Mean 65 Differential Selection Experimental Mortality (Attrition) Treatment Spillover 67 69 71 Additive and Interactive Effects 73 Threats to External Validity “* 75 Under the Bonnet of Threats to External Validity 77 Increasing the External Validity of a Test Overcoming the Threats to External Validity Through Replications 82 and Diversification Distinctions Between Laboratory and Field Trials 85 85 One Final Point About the Connection Between Treatment Integrity and External Validity 4 87 Conclusion 88 T is for Trials (or Tests) 91 Different Kinds of Trials 92 Pre-Experimental Designs Design 1: The One-Shot Case Study The One-Group Pre-test-Post-test Design The Static-Group Comparison Design True Experimental Designs 95 95 96 99 100 The Pre-test-Post-Test Control Group Design 100 The Post-Test-Only Control Group Design 105 The Solomon Four-Group Design 106 Quasi-Experimental Designs 108 Why You Might Not Be Able to Conduct a Pre-Experiment or True Experiment 108 The (Interrupted) Time-Series Experiment 110 The Multiple Time-Series Design 112 The Equivalent Time-Samples Design 113 The Non-Equivalent Control Group Design 114
CONTENTS 5 6 The Separate-Sample Pre-test-Post-test Design Regression Discontinuity Design Propensity Score Matching Conclusion 115 116 118 119 Running Experimental Designs 123 Recipes for Experiments Experimental Protocols and Quality Control Tools A Closer Look at the Benefits ofProtocols as a Quality Control Tool What Should Be Included in the Experimental Protocol? Protocols for Reporting the Findings of the Experiment Implementation of Experiments Researcher-Practitioner Coalitions Ethics in Experiments A Template for a General Assessment of Ethics in Experimental Designs Conclusion Appendix: CrimPORT Template 124 124 125 128 132 136 136 140 Conclusions and Final Remarks 155 Not All Experimental Designs Are Created Equal; Choose the Most Appropriate Wisely The Future of Experimental Disciplines Proliferation Diversification Collaboration How Do We Mainstream Experiments Into Policymaking Processes? 158 160 160 161 161 162 Glossary References Index 142 144 146 165 169 219
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| adam_txt |
CONTENTS List of Figures, Tables and Boxes About the Authors 1 2 Introduction xi xiii 1 Contextualising Randomised Experiments in a Wide Range of Causal Designs Causal Designs and the Scientific Meaning of Causality Why Should Governments and Agencies Care About Causal Designs? 7 9 11 R is for Random 15 Comparisons in Science Counterfactuals Randomisation Procedures for Random Assignment (How to Randomise) Simple Random Assignment Alternatives to Simple Random Assignment: Restrictive Allocation The Randomised Block Design Trickle Flow Random Assignment Matched Pairs Design Minimisation Randomisation in Practice: The 'Randomiser' Units of Randomisation (What to Randomise?) Person-Based Randomisation Place-Based Randomisation Temporal-Based Randomisation A Final Word Regarding the Choice of Units of Randomisation Should We Use Significance Tests for Baseline Imbalances After Randomisation? Inferential Statistics and Probability Theory Randomisation and Sample Size Considerations Summarising the Benefits of Randomisation 16 17 20 22 23 25 26 29 31 35 36 36 37 39 41 42 44 46 48 50
viil 3 EXPERIMENTAL DESIGNS C is for Control 53 What Do We Mean by Control? 54 Threats to Internal Validity 54 History Maturation 58 60 Testing Instrumentation 61 63 Statistical Regression to the Mean 65 Differential Selection Experimental Mortality (Attrition) Treatment Spillover 67 69 71 Additive and Interactive Effects 73 Threats to External Validity “* 75 Under the Bonnet of Threats to External Validity 77 Increasing the External Validity of a Test Overcoming the Threats to External Validity Through Replications 82 and Diversification Distinctions Between Laboratory and Field Trials 85 85 One Final Point About the Connection Between Treatment Integrity and External Validity 4 87 Conclusion 88 T is for Trials (or Tests) 91 Different Kinds of Trials 92 Pre-Experimental Designs Design 1: The One-Shot Case Study The One-Group Pre-test-Post-test Design The Static-Group Comparison Design True Experimental Designs 95 '95 96 99 100 The Pre-test-Post-Test Control Group Design 100 The Post-Test-Only Control Group Design 105 The Solomon Four-Group Design 106 Quasi-Experimental Designs 108 Why You Might Not Be Able to Conduct a Pre-Experiment or True Experiment 108 The (Interrupted) Time-Series Experiment 110 The Multiple Time-Series Design 112 The Equivalent Time-Samples Design 113 The Non-Equivalent Control Group Design 114
CONTENTS 5 6 The Separate-Sample Pre-test-Post-test Design Regression Discontinuity Design Propensity Score Matching Conclusion 115 116 118 119 Running Experimental Designs 123 Recipes for Experiments Experimental Protocols and Quality Control Tools A Closer Look at the Benefits ofProtocols as a Quality Control Tool What Should Be Included in the Experimental Protocol? Protocols for Reporting the Findings of the Experiment Implementation of Experiments Researcher-Practitioner Coalitions Ethics in Experiments A Template for a General Assessment of Ethics in Experimental Designs Conclusion Appendix: CrimPORT Template 124 124 125 128 132 136 136 140 Conclusions and Final Remarks 155 Not All Experimental Designs Are Created Equal; Choose the Most Appropriate Wisely The Future of Experimental Disciplines Proliferation Diversification Collaboration How Do We Mainstream Experiments Into Policymaking Processes? 158 160 160 161 161 162 Glossary References Index 142 144 146 165 169 219 |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:39:26Z |
| indexdate | 2024-07-10T09:16:06Z |
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| isbn | 9781526426628 |
| language | English |
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