In nursing research, accurate and reliable data analysis is essential for drawing meaningful conclusions. Multicollinearity can lead to incorrect estimates of the relationships between variables, potentially resulting in flawed decision-making. By identifying and addressing high VIF values, researchers can ensure more accurate and reliable analyses, which ultimately contribute to better patient care and clinical outcomes.
