Late Entries, Missing Items: Using Timestamp Paradata to Detect Underreporting in a Diary Survey

Thomas M. Menino Convention & Exhibition Center 

Accurate measurement of household food acquisitions is critical for understanding food purchasing behavior and sufficiency, yet underreporting remains a persistent challenge in diary-based surveys. This paper examines whether timestamp paradata from the USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) food log diary can be used to predict underreporting of food acquisitions and items. Specifically, temporal patterns in diary completion, such as long lags between food events and recorded entries, are analyzed to assess whether these behaviors are associated with subsequent admissions of forgotten or omitted acquisitions in a post-diary recall survey. Using linked diary, recall, and paradata records from FoodAPS, empirical relationships are estimated between diary completion timing and indicators of underreporting, including self-reported omissions and discrepances in reported acquisition counts. The results highlight the potential value of paradata as a diagnostic tool for identifying underreporting risk in near real time, with implications for adaptive survey design, targeted prompts, and post-survey adjustment strategies that can enhance data quality.

Paradata

Measurement Error

Underreporting

Diary-Based Surveys

Process Data

Data Quality 

Survey Research Methods Section