Measurement Error and Its Impact on Partial Correlation and Multiple Linear Regression Analyses1

In studies examining associations between dietary factors and biomedical risk factors, the relations, if they exist, are frequently attenuated by measurement error. Measurement error may be due to a large intraindividual variation and an inadequate number of measurements or to an inaccurate measuring instrument. This paper evaluates the impact of measurement error on partial correlation and multiple linear regression analyses. Quantitative methods are derived to estimate the potential attenuation of associations. The results indicate that when the controlled variables do not have measurement error, but the correlated variables do, the attenuation of the partial correlation coefficient (or multiple regression coefficient) is greater than that of the simple correlation (or regression) coefficient. When both the correlated variables and the controlled variables have measurement error, the partial correlation (or the regression) coefficients can be either increased or decreased.