Data Triangulation

Data triangulation is when a piece of data or a finding can be verified with several different research methods or data sources, adding credibility to the findings.

  • Requires planning, preferably prior to data collection
  • Uses different data sources across different levels and time periods
    • Linkage over time (panel data) is done to examine program impacts while controlling for individual-level factors at the outset.
    • Linkage of couple-level data can be done, although there are both advantages and disadvantages to this approach.
    • Linkage of mother and child data is often done; linkage to father’s data is more difficult.
  • Survey data sets (for example, household and facility information) can be linked to:
    • compare level of health services availability to health outcomes across geographical units
    • examine the effects of physical attributes on service utilization
    • create time series and panel data to help build causal explanations of program effects

In some cases, it is not appropriate to link data.

  • It may not be necessary for some programs in a given context.
  • If done with improper methodology or data sources, linking data can provide inaccurate findings.
  • Linked analysis is more appropriate for evaluation than for monitoring.

 

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