An Investigation of the Factors Affecting the Vertical Scaling of Multidimensional Mixed-Format Tests

Abstract

This study examined the effect of the structure of a common item set (only dichotomous common items – mixed-format common item sets), parameter estimation methods and scale shrinkage on vertical scaling results when multidimensional datasets were used within the context of Common Item Nonequivalent Group (CINEG) design. Interactions between these variables were also investigated. The study was performed using simulated data. Measurement error and bias indexes were used to evaluate the quality of vertical scaling. All the procedures used in the data analysis were replicated 50 times to increase the generalizability of the results. R program was used for the data generation, calibration of the parameters and vertical scaling procedures. Possible interactions were investigated with factorial analysis of variance by using SPSS. The results showed a consistent effect of the common item format in all conditions. In addition, some interactions between the variables were observed. These findings are discussed and some recommendations are provided.