In this study, the effect of different error structures on psedounivariate and multivariate analytical figures of merit in simulated data of hyphenated chromatographic systems was investigated. Different error structures (e.g., homoscedastic, heteroscedastic, and correlated) were investigated. For this purpose, five components systems at five concentration levels with three replicates were simulated. Different types of error were added to the data. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Maximum Likelihood Principal Component Analysis (MLPCA-MCR-ALS) methods