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Development Research in Practice : The DIME Analytics Data Handbook.

Bibliographic Details
Main Author: Bjärkefur, Kristoffer.
Other Authors: Cardoso de Andrade, Luíza., Daniels, Benjamin., Jones, Maria Ruth.
Format: eBook
Language:English
Published: Hauppauge : World Bank Publications, 2021.
Edition:1st ed.
Subjects:
Data curation.
Business > Data processing > Management.
Economic development > Research > Methodology.
Electronic books.
Online Access:Click to View
Table of Contents:
  • 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.

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