Several factors can contribute to statistically insignificant results in epidemiological research:
Small Sample Size: A small sample size can reduce the power of a study, making it difficult to detect a true effect even if one exists. High Variability:High variability in the data can obscure potential associations, leading to insignificant findings. Measurement Error: Errors in data collection or measurement can introduce noise, diminishing the ability to detect significant results. Confounding Variables: Uncontrolled confounding variables can mask true associations, resulting in insignificant outcomes.
