Development research in practice : the DIME analytics data handbook
| Development research in practice : the DIME analytics data handbook |
| Autore | Bjärkefur Kristoffer |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | , : World Bank Publications, , 2021 |
| Descrizione fisica | 1 online resource (231 pages) |
| Disciplina | 658.4038 |
| Altri autori (Persone) |
Cardoso de AndradeLuíza
DanielsBenjamin JonesMaria Ruth |
| Soggetto topico |
Business - Data processing - Management
Data curation Economic development - Research - Methodology |
| ISBN | 1-4648-1695-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover -- Contents -- Foreword -- Acknowledgments -- About the Authors -- Abbreviations -- Introduction -- How to read this book -- The DIME Wiki: A complementary resource -- Standardizing data work -- Standardizing coding practices -- The team behind this book -- Looking ahead -- References -- Chapter 1 Conducting reproducible, transparent, and credible research -- Developing a credible research project -- Conducting research transparently -- Analyzing data reproducibly and preparing a reproducibility package -- Looking ahead -- References -- Chapter 2 Setting the stage for effective and efficient collaboration -- Preparing a collaborative work environment -- Organizing code and data for replicable research -- Preparing to handle confidential data ethically -- Looking ahead -- References -- Chapter 3 Establishing a measurement framework -- Documenting data needs -- Translating research design to data needs -- Creating research design variables by randomization -- Looking ahead -- References -- Chapter 4 Acquiring development data -- Acquiring data ethically and reproducibly -- Collecting high-quality data using electronic surveys -- Handling data securely -- Looking ahead -- References -- Chapter 5 Cleaning and processing research data -- Making data "tidy" -- Implementing data quality checks -- Processing confidential data -- Preparing data for analysis -- Looking ahead -- References -- Chapter 6 Constructing and analyzing research data -- Creating analysis data sets -- Writing analysis code -- Creating reproducible tables and graphs -- Increasing efficiency of analysis with dynamic documents -- Looking ahead -- References -- Chapter 7 Publishing reproducible research outputs -- Publishing research papers and reports -- Preparing research data for publication -- Publishing a reproducible research package -- Looking ahead -- References. Chapter 8 Conclusion -- Bringing it all together -- Where to go from here -- Appendix A: The DIME Analytics Coding Guide -- Appendix B: DIME Analytics resource directory -- Appendix C: Research design for impact evaluation -- Boxes -- Box I.1 The Demand for Safe Spaces case study -- Box 1.1 Summary: Conducting reproducible, transparent, and credible research -- Box 1.2 Registering studies: A case study from the Demand for Safe Spaces project -- Box 1.3 Writing preanalysis plans: A case study from the Demand for Safe Spaces project -- Box 1.4 Preparing a reproducibility package: A case study from the Demand for Safe Spaces project -- Box 2.1 Summary: Setting the stage for effective and efficient collaboration -- Box 2.2 Preparing a collaborative work environment: A case study from the Demand for Safe Spaces project -- Box 2.3 Organizing files and folders: A case study from the Demand for Safe Spaces project -- Box 2.4 DIME master do-file template -- Box 2.5 Writing code that others can read: A case study from the Demand for Safe Spaces project -- Box 2.6 Writing code that others can run: A case study from the Demand for Safe Spaces project -- Box 2.7 Seeking ethical approval: An example from the Demand for Safe Spaces project -- Box 2.8 Obtaining informed consent: A case study from the Demand for Safe Spaces project -- Box 2.9 Ensuring the privacy of research subjects: An example from the Demand for Safe Spaces project -- Box 3.1 Summary: Establishing a measurement framework -- Box 3.2 Developing a data linkage table: An example from the Demand for Safe Spaces project -- Box 3.3 Creating data flowcharts: An example from the Demand for Safe Spaces project -- Box 3.4 An example of uniform-probability random sampling -- Box 3.5 An example of randomized assignment with multiple treatment arms -- Box 3.6 An example of reproducible randomization. Box 4.1 Summary: Acquiring development data -- Box 4.2 Determining data ownership: A case study from the Demand for Safe Spaces project -- Box 4.3 Piloting survey instruments: A case study from the Demand for Safe Spaces project -- Box 4.4 Checking data quality in real time: A case study from the Demand for Safe Spaces project -- Box 5.1 Summary: Cleaning and processing research data -- Box 5.2 Establishing a unique identifier: A case study from the Demand for Safe Spaces project -- Box 5.3 Tidying data: A case study from the Demand for Safe Spaces project -- Box 5.4 Assuring data quality: A case study from the Demand for Safe Spaces project -- Box 5.5 Implementing de-identification: A case study from the Demand for Safe Spaces project -- Box 5.6 Correcting data points: A case study from the Demand for Safe Spaces project -- Box 5.7 Recoding and annotating data: A case study from the Demand for Safe Spaces project -- Box 6.1 Summary: Constructing and analyzing research data -- Box 6.2 Integrating multiple data sources: A case study from the Demand for Safe Spaces project -- Box 6.3 Creating analysis variables: A case study from the Demand for Safe Spaces project -- Box 6.4 Documenting variable construction: A case study from the Demand for Safe Spaces project -- Box 6.5 Writing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.6 Organizing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.7 Visualizing data: A case study from the Demand for Safe Spaces project -- Box 6.8 Managing outputs: A case study from the Demand for Safe Spaces project -- Box 7.1 Summary: Publishing reproducible research outputs -- Box 7.2 Publishing research papers and reports: A case study from the Demand for Safe Spaces project -- Box 7.3 Publishing research data sets: A case study from the Demand for Safe Spaces project. Box 7.4 Releasing a reproducibility package: A case study from the Demand for Safe Spaces project -- Figures -- Figure I.1 Overview of the tasks involved in development research data work -- Figure B2.3.1 Folder structure of the Demand for Safe Spaces data work -- Figure B3.3.1 Flowchart of a project data map -- Figure B4.4.1 A sample dashboard of indicators of progress -- Figure 4.1 Data acquisition tasks and outputs -- Figure 5.1 Data-cleaning tasks and outputs -- Figure 6.1 Data analysis tasks and outputs -- Figure 7.1 Publication tasks and outputs -- Figure 8.1 Research data work outputs. |
| Altri titoli varianti | Development Research in Practice |
| Record Nr. | UNINA-9910794504303321 |
Bjärkefur Kristoffer
|
||
| , : World Bank Publications, , 2021 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Development research in practice : the DIME analytics data handbook
| Development research in practice : the DIME analytics data handbook |
| Autore | Bjärkefur Kristoffer |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | , : World Bank Publications, , 2021 |
| Descrizione fisica | 1 online resource (231 pages) |
| Disciplina | 658.4038 |
| Altri autori (Persone) |
Cardoso de AndradeLuíza
DanielsBenjamin JonesMaria Ruth |
| Soggetto topico |
Business - Data processing - Management
Data curation Economic development - Research - Methodology |
| ISBN | 1-4648-1695-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover -- Contents -- Foreword -- Acknowledgments -- About the Authors -- Abbreviations -- Introduction -- How to read this book -- The DIME Wiki: A complementary resource -- Standardizing data work -- Standardizing coding practices -- The team behind this book -- Looking ahead -- References -- Chapter 1 Conducting reproducible, transparent, and credible research -- Developing a credible research project -- Conducting research transparently -- Analyzing data reproducibly and preparing a reproducibility package -- Looking ahead -- References -- Chapter 2 Setting the stage for effective and efficient collaboration -- Preparing a collaborative work environment -- Organizing code and data for replicable research -- Preparing to handle confidential data ethically -- Looking ahead -- References -- Chapter 3 Establishing a measurement framework -- Documenting data needs -- Translating research design to data needs -- Creating research design variables by randomization -- Looking ahead -- References -- Chapter 4 Acquiring development data -- Acquiring data ethically and reproducibly -- Collecting high-quality data using electronic surveys -- Handling data securely -- Looking ahead -- References -- Chapter 5 Cleaning and processing research data -- Making data "tidy" -- Implementing data quality checks -- Processing confidential data -- Preparing data for analysis -- Looking ahead -- References -- Chapter 6 Constructing and analyzing research data -- Creating analysis data sets -- Writing analysis code -- Creating reproducible tables and graphs -- Increasing efficiency of analysis with dynamic documents -- Looking ahead -- References -- Chapter 7 Publishing reproducible research outputs -- Publishing research papers and reports -- Preparing research data for publication -- Publishing a reproducible research package -- Looking ahead -- References. Chapter 8 Conclusion -- Bringing it all together -- Where to go from here -- Appendix A: The DIME Analytics Coding Guide -- Appendix B: DIME Analytics resource directory -- Appendix C: Research design for impact evaluation -- Boxes -- Box I.1 The Demand for Safe Spaces case study -- Box 1.1 Summary: Conducting reproducible, transparent, and credible research -- Box 1.2 Registering studies: A case study from the Demand for Safe Spaces project -- Box 1.3 Writing preanalysis plans: A case study from the Demand for Safe Spaces project -- Box 1.4 Preparing a reproducibility package: A case study from the Demand for Safe Spaces project -- Box 2.1 Summary: Setting the stage for effective and efficient collaboration -- Box 2.2 Preparing a collaborative work environment: A case study from the Demand for Safe Spaces project -- Box 2.3 Organizing files and folders: A case study from the Demand for Safe Spaces project -- Box 2.4 DIME master do-file template -- Box 2.5 Writing code that others can read: A case study from the Demand for Safe Spaces project -- Box 2.6 Writing code that others can run: A case study from the Demand for Safe Spaces project -- Box 2.7 Seeking ethical approval: An example from the Demand for Safe Spaces project -- Box 2.8 Obtaining informed consent: A case study from the Demand for Safe Spaces project -- Box 2.9 Ensuring the privacy of research subjects: An example from the Demand for Safe Spaces project -- Box 3.1 Summary: Establishing a measurement framework -- Box 3.2 Developing a data linkage table: An example from the Demand for Safe Spaces project -- Box 3.3 Creating data flowcharts: An example from the Demand for Safe Spaces project -- Box 3.4 An example of uniform-probability random sampling -- Box 3.5 An example of randomized assignment with multiple treatment arms -- Box 3.6 An example of reproducible randomization. Box 4.1 Summary: Acquiring development data -- Box 4.2 Determining data ownership: A case study from the Demand for Safe Spaces project -- Box 4.3 Piloting survey instruments: A case study from the Demand for Safe Spaces project -- Box 4.4 Checking data quality in real time: A case study from the Demand for Safe Spaces project -- Box 5.1 Summary: Cleaning and processing research data -- Box 5.2 Establishing a unique identifier: A case study from the Demand for Safe Spaces project -- Box 5.3 Tidying data: A case study from the Demand for Safe Spaces project -- Box 5.4 Assuring data quality: A case study from the Demand for Safe Spaces project -- Box 5.5 Implementing de-identification: A case study from the Demand for Safe Spaces project -- Box 5.6 Correcting data points: A case study from the Demand for Safe Spaces project -- Box 5.7 Recoding and annotating data: A case study from the Demand for Safe Spaces project -- Box 6.1 Summary: Constructing and analyzing research data -- Box 6.2 Integrating multiple data sources: A case study from the Demand for Safe Spaces project -- Box 6.3 Creating analysis variables: A case study from the Demand for Safe Spaces project -- Box 6.4 Documenting variable construction: A case study from the Demand for Safe Spaces project -- Box 6.5 Writing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.6 Organizing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.7 Visualizing data: A case study from the Demand for Safe Spaces project -- Box 6.8 Managing outputs: A case study from the Demand for Safe Spaces project -- Box 7.1 Summary: Publishing reproducible research outputs -- Box 7.2 Publishing research papers and reports: A case study from the Demand for Safe Spaces project -- Box 7.3 Publishing research data sets: A case study from the Demand for Safe Spaces project. Box 7.4 Releasing a reproducibility package: A case study from the Demand for Safe Spaces project -- Figures -- Figure I.1 Overview of the tasks involved in development research data work -- Figure B2.3.1 Folder structure of the Demand for Safe Spaces data work -- Figure B3.3.1 Flowchart of a project data map -- Figure B4.4.1 A sample dashboard of indicators of progress -- Figure 4.1 Data acquisition tasks and outputs -- Figure 5.1 Data-cleaning tasks and outputs -- Figure 6.1 Data analysis tasks and outputs -- Figure 7.1 Publication tasks and outputs -- Figure 8.1 Research data work outputs. |
| Altri titoli varianti | Development Research in Practice |
| Record Nr. | UNINA-9910815166803321 |
Bjärkefur Kristoffer
|
||
| , : World Bank Publications, , 2021 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||