The Data Mining Work Stream seeks to build and expand upon previous Phase III efforts to improve the evidence base for food assistance for nutrition research and programming.
This Work Stream is comprised of three discrete but related data mining activities:
FAQR Field Study Analysis –
Work with USAID/BHA partners to develop additional research questions that could be explored by conducting additional secondary data analysis on data collected as part of three previous FAQR field studies conducted in Malawi, Burkina Faso, and Sierra Leone.
Conduct exploratory analyses with the qualitative and quantitative field study data, possibly including pooled data from more than one study, focused on thematic areas related to quality of feeding and care in the household, child growth, and quality of programming in supplemental and blanket feeding programs
Aggregate key findings from previous FAQR field study analyses with new data mining analyses and offer relevant recommendations for future research and programming for USAID/BHA.
USAID/BHA Population-Based Survey Dataset Harmonization and Pooling –
The goal of this review is to examine the possibility of tapping into the unrealized potential of PBS data collected at project baseline and endline to deepen USAID’s understanding of program effectiveness and its determinants. The datasets were drawn from the baseline and endline evaluations of 13 USAID-funded Development Food Security Activities (DFSAs) between 2012 and 2019. Specific goals of the review are:
Demonstrate how the standardization of data collection and reportingcan facilitate future efforts by USAID to harmonize and pool datasets.
Enhance USAID’s understanding of how pooled PBS data could inform future programming and policy decisions.
Provide a more nuanced understanding of the effectiveness of DFSAs based on its own PBS data and calibrate the expectations of USAID/Bureau for Humanitarian Assistance (BHA) regarding DFSA outcomes.
Analysis of Research Publications Archived on the Research Engagement on Food Interventions for Nutritional Effectiveness (REFINE) Database –
Locate and obtain open access primary datasets from published research studies catalogued in the REFINE database in the last 5 years.
Compare study designs and open access datasets to identify research questions with the potential to be addressed by pooled/meta-analyses.
Compile and harmonize datasets in a standard format conducive to such analyses.
Provide insight and recommendations for future data-sharing practices and policies to be considered by USAID and other research funders.
Field Study Data Mining Report
- Additional Analysis of Two Field Studies Comparing Four Supplementary Foods for Treatment or Prevention of Malnutrition
REFINE Open-Access Data Mining Report
BHA Population Based Survey (PBS) Data Mining Report
- Population-Based Survey (PBS) Dataset Harmonization and Pooling- Potential Value to USAID and Challenges
Work Stream Contact
Contact the FAQR Team at email@example.com