Title page
Contents
Why this guide 8
Who should use this guide 9
How this guide is organized 9
Keeping the big picture in mind 11
Section I: Disclosure Risk Management 12
Ensuring authorization to share data 12
Assessing disclosure risk in data files 13
Step 1: List variables in the data files that directly identify an individual 14
Step 2: List potential indirect identifiers 14
Step 3: Examine cell sizes of indirect identifiers (individually and in combination), and flag small cell sizes for disclosure risk mitigation 15
Step 4: Identify variables that contain information of a sensitive nature 15
Mitigating disclosure risk in data files 15
Step 1: Assess feasibility of technical solutions to mitigate disclosure risk, and examine their impact on the usefulness of the dataset 16
Step 2: If needed, mitigate disclosure risk by restricting access to the data 19
Additional resources about disclosure risk management 19
Background on methods for assessing and mitigating disclosure risk 19
How-to guides for researchers 20
Statistical software program 21
Disclosure risk management for qualitative text data 21
Section II: Data documentation and organization 22
Organizing data management processes and documentation 22
Data management processes 22
Documenting study decisions on an ongoing basis 23
Developing a data file structure and documentation for the shared dataset 24
Step 1: Develop a data file structure 24
Step 2: Review programming code for organization, clarity, completeness, and disclosure risk 25
Step 3: Prepare a Description of Data Files document 26
Step 4: Provide documentation and/or code when data cannot be shared 27
Additional resources about data organization and documentation 27
Guides 27
PowerPoint 28
Video presentations and podcasts 28
Organizing and documenting qualitative data 28
Section III: Depositing the dataset 30
Data repositories 30
Data repositories of special interest to education researchers 32
Alternatives to data repositories 34
When to deposit data 35
Additional resource about depositing the dataset 35
Reference document 35
Section IV: Checklist of key steps for data sharing 36
References 39
Appendix A: Methods and measures template 40
Project Description and Research Design Overview 40
Participants 40
Intervention(s) 41
Procedures 41
Measures 42
Data Analysis 42
Summary of Information Needed for What Works Clearinghouse reviews 43
Appendix B.1: Sample programming code file structure and contents 46
Organizing programming code files 46
Best practices for organizing and documenting code 47
Meaningful and clear documentation in the code 48
Structuring code for readability and visual clarity 48
Appendix B.2: Sample outline for a description of data files document 49
I. Introduction 49
II. Study Design 49
III. Data Sources 49
IV. Data Files 50
Data file preparation 50
Detailed descriptions of files or related groups of files 50
Missing data 50
Data file details 50
V. Appendix 51
Appendix B.3: Sample codebook, annotated data collection instrument, and summary statistics 52
Codebook 52
Annotated data collection instrument 53
Summary statistics document 54
Appendix B.4: Sample description of data files 56
Excerpted Sections from The effectiveness of secondary math teachers from Teach for America and Teaching Fellows programs description of data files 56
A. Study design 56
B. Data sources 61
C. Data files 63
Table 1. Steps to prepare data for sharing occur across the study lifecycle 10
Table 2. At-a-glance summary of data repositories 33
Figure 1. A simple file structure with many ways to link files 25
Boxes
Box 1. Federal policies on open access to research and data 8
Box 2. IES resources on public access to data 9
Box 3. Using this guide to develop a Data Management Plan for a new study 10
Box 4. Key definitions 12
Box 5. Resources on participant consent and data sharing 13
Box 6. Analytic and raw (source) data files 14
Box 7. Methods and measures template 23
Box 8. Resources for documenting and organizing data files and code 27
Box 9. Example of depositing study data with a school district 34
Table A.1. Information to include for each outcome measure, time point, and comparison 43
Table A.2. Additional data to include for RCTs that assigned individuals to the intervention and comparison groups 43
Table A.3. Additional sample sizes to include for all studies that assigned clusters to the intervention and comparison groups 44
Table A.4. Additional sample sizes to include for RCTs that assigned clusters to the intervention and comparison groups 44
Table A.5. Data to include for each pre-intervention measure for which any observations are missing or imputed in the analytic sample and each... 45
Table B.3.1. Codebook example for a school-level data file 52
Table B.4.1. Number of States, Districts, Schools, Classroom Matches, Teachers, and Classes in the Study 59
Table B.4.2. Number of Students in the Study 61
Table B.4.3. Data Sources for the Evaluation 62
Table B.4.4. Datasets Included in the Restricted-Use Files 64
Table B.4.5. Types of Missing Data Values 66
Table B.4.6. Organization of Restricted-Use Files 67
Appendix Boxes
Box B.1.1. Organize programming code files and data files in directories 47