Several factors can increase the likelihood of Type II errors in epidemiological studies: 1. Sample Size: Smaller sample sizes reduce the power of a study, making it less likely to detect true associations. 2. Effect Size: Smaller effect sizes are harder to detect and may require larger samples to achieve sufficient power. 3. Measurement Error: Inaccurate measurement of exposures or outcomes can obscure true associations. 4. Confounding Variables: Failure to control for confounding variables can lead to incorrect conclusions. 5. Study Design: Poorly designed studies are more prone to Type II errors.
