On basis of this, we suggest that the importance of the epidemiological aspects on data quality of field data should be articulated and emphasised in the education of veterinarians, both at student and post-graduate level.
However, reducing inter-instrument variability through technical/mechanical calibration would only be important in order to improve field data quality and study power if random variability across units contributed considerably to the total variation in field data.
Potentially, unit-specific in-vitro calibration of accelerometers could increase field data quality and study power.
Key challenges during the monitoring were: (1) motivating household members to purchase the improved cookstoves (ICSs); (2) ensuring that the households made the transition to using the ICSs; and (3) maintaining high standards of data quality as a field team.
While we assessed data quality of select fields through client surveys, this approach did not allow us to examine accuracy of fields critical to vaccine safety, such as lot number and adverse events and was thus a limitation of this evaluation.
INS responsibilities included collaboration on protocol development, assessment tool drafting and pre-testing, field team recruitment, quantitative and qualitative data collection, field logistics, data entry, data transcription, and data quality assurance in the field.
It includes evaluation of data quality, effective data coverage, field reconstruction error and model nowcast error.
Riparian quality field data was obtained using the Riparian Quality Index.
We suggest that a greater number of high quality field data in dense tropical forest can mitigate this issue.
A simple new shoreline change model has been developed and calibrated/evaluated with several sets of high quality field data.
