How Does Inadequate Data Quality Affect Epidemiological Studies?
Poor data quality can have several detrimental effects on epidemiological studies, including:
Bias: Systematic errors that lead to incorrect estimates of associations between exposures and outcomes. Reduced Power: Incomplete data can reduce the statistical power of a study, making it harder to detect true associations. Invalid Inferences: Inaccurate data can lead to incorrect conclusions and recommendations, potentially causing harm if these are implemented in public health policy. Wasted Resources: Poor-quality data can result in inefficient use of time, money, and effort, as well as the need for additional studies to confirm or refute findings.
