Loss of data can have several adverse effects on epidemiological research:
Bias: Missing data can introduce systematic errors, leading to biased estimates and invalid conclusions. Reduced statistical power: Incomplete data sets lower the ability to detect true associations between variables. Generalizability issues: If data loss is not random, the remaining sample may not be representative of the population, limiting the generalizability of findings. Increased uncertainty: Missing data can increase the variability of estimates, making results less reliable.
