Reliability testing is important because it determines the dependability of measurement tools. In epidemiology, where researchers often deal with large datasets and longitudinal studies, reliable measurements are essential for drawing accurate inferences. Unreliable data can lead to bias and confounding, thereby compromising the integrity of the study.
