There are some studies in the literature that have considered the impact of modeling multidimensional mixed structured tests as unidimensional. These studies have demonstrated that the error associated with the discrimination parameters increases as the correlation between dimensions increases. In this study, the interaction between items' angles on coordinate system and the correlations between dimensions was investigated when estimating multidimensional tests as unidimensional. Data were simulated based on two dimensional, and two-parameter compensatory MIRT model. Angles of items were determined as 0.15 degrees; 0.30 degrees; 0.45 degrees; 0.60 degrees and 0.75 degrees respectively. The correlations between ability parameters were set to 0.15, 0.30, 0.45, 0.60 and 0.75 respectively, which are same with the angles of discrimination parameters. The ability distributions were generated from standard normal, positively and negatively skewed distributions. A total of 75 (5 x 5 x 3) conditions were studied: five different conditions for the correlation between dimensions; five different angles of items and three different ability distributions. For all conditions, the number of items was fixed at 25 and the sample size was fixed at n = 2,000. Item and ability parameter estimation were conducted using BILOG. For each condition, 100 replications were performed. The RMSE statistic was used to evaluate parameter estimation errors, when multidimensional response data were scaled using a unidimensional IRT model. Based on the findings, it can be concluded that the pattern of RMSE values especially for discrimination parameters are different from the existing studies in the literature in which multidimensional tests were estimated as unidimensional.