This study aims to compare item and student parameters of dichotomously scored multidimensional constructs estimated based on unidimensional and multidimensional Item Response Theory (IRT) under different conditions of sample size, interdimensional correlation and number of dimensions. This research, conducted with simulations, is of a basic nature. The standard errors of the item and student parameters estimated according to both models were evaluated by the mean of the error squares. The results of the study indicate that there is no significant difference between the errors of the item parameters obtained from the unidimensional and multidimensional IRT in the cases of two-dimensional data structures and high interdimensional correlations. However, when the data structure are three and five dimensional, the item parameter errors resulting from the unidimensional IRT increase. Standard errors for item parameters decreased as the sample size increased. When the standard errors arising from ability parameters were analysIRTed, it was observed that multidimensional IRT estimated with lower errors for all conditions. As a result of the study, it is established that multidimensional IRT provides more accurate results in the analysis of multidimensional constructs, especially in the estimation of student parameters and in making decisions about students. Therefore, it is recommended that multidimensional models should be used for student ability estimation in national and international large-scale examinations.