Incomplete data can lead to several problems in epidemiological research. These include:
Bias: Missing data can introduce various types of bias, such as selection bias or information bias, which can distort study findings. Reduced Statistical Power: The loss of data points can reduce the study's ability to detect significant associations or effects. Misleading Conclusions: Drawing conclusions from incomplete data can lead to incorrect or misleading results, affecting public health policies and interventions. Generalizability: Incomplete data can limit the extent to which findings can be generalized to the wider population.
