Development Research in Practice: The DIME Analytics Data Handbook. By Kristoffer Bjärkefur, Luíza Cardoso de Andrade, Benjamin Daniels, and Maria Jones
The following paragraph was in the quality checks section. I'm now not sure whether it's a better fit to the data acquisition chapter or the data cleaning
\subsection{Finalizing data collection}
When all data collection is complete, the survey team should prepare a final field report,
which should report reasons for any deviations between the original sample and the dataset collected.
Identification and reporting of \textbf{missing data} and \textbf{attrition}
is critical to the interpretation of survey data.
It is important to structure this reporting in a way that not only
groups broad rationales into specific categories
but also collects all the detailed, open-ended responses
to questions the field team can provide for any observations that they were unable to complete.
This reporting should be validated and saved alongside the final raw data, and treated the same way.
This information should be stored as a dataset in its own right
-- a \textbf{tracking dataset} -- that records all events in which survey substitutions
and attrition occurred in the field and how they were implemented and resolved.
The following paragraph was in the quality checks section. I'm now not sure whether it's a better fit to the data acquisition chapter or the data cleaning