Data quality can be assessed using various metrics and techniques. Audits and validation studies can be conducted to compare collected data against a known standard or a gold standard. Statistical methods can also be employed to identify anomalies and inconsistencies. Sensitivity analyses can help determine the robustness of findings against potential data errors.
