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Activity B: Produce a question analysis framework

Based on your review, produce a question analysis framework which sets out for each question:

  • The available and accessible data, its source and quality, noting data gaps.
  • The methods to be used for analysis and the time required.
  • The tools and software required.
  • The human skills required.

Refer to the examples of data mapping/questions analysis frameworks below.

Based on this high-level assessment of the technical feasibility, the NIPN policy experts and NIPN data experts will decide together on the final ranking of the full set of policy questions on which the NIPN team will work at the top. The question analysis framework makes it possible to document and keep track of the questions that can and will be answered completely or partially by NIPN, or others, and which questions have lower priority and for which the time and human resources’ investment is not feasible.

Prior to beginning data analysis, the NIPN data experts will need to work out a much more detailed data analysis plan to guide the work of the NIPN data experts. This is further described in the guidance note on data analysis (see section 3.4).

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Example of data mapping in a fictional country
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Example of question analysis framework in Mali (from the NEP)

Priority question n°1: "What are the reasons for the Mopti region presenting lower level indicators in relation to mother and child health and nutrition than the other regions according to the EDHS-V (2015-2016)"

Sub-questionsData sourcesMethodsToolsSkills & capacity needs
Which MCHN indicators of the DHS-V are lower in Mopti than in other regions? DHS-V Calculate each indicator level with confidence interval in each region
Difference testing between Mopti and other regions
STATA
Protocol for survey data
Protocol for data comparison
Calculation of confidence intervals with STATA
Comparison between regions with STATA
How do the MCHN indicators of the DHS-V in the health districts of Mopti compare to the health districts of other regions? Database DHS-V paired with GPS data Data disaggregation by region and district
Estimate level of coverage indicator with confidence interval for each district (homogeneisation)
Comparison of indicators level between Mopti and other districts
STATA
Disaggregation protocol for DHS data
Data homogeneisation protocol
Protocol for data comparison
Use of the various protocols (disaggregation, homogeneisation, comparison)
For those MCHN indicators, what are the trends for the regions and health districts of Mali according to the various surveys (2001 to 2013)