Reise, Cook, and Moore (under review) proposed a "comparison modeling" approach to assess the distortion in item parameter estimates when a unidimensional item response theory (IRT) model is imposed on multidimensional data. Central to their approach is the comparison of item slope parameter estimates from a unidimensional IRT model (a restricted model), with the item slope parameter estimates from the general factor in an exploratory bifactor IRT model (the unrestricted comparison model). In

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... rn, these authors suggested that the unrestricted comparison bifactor model be derived from a target factor rotation (Browne, 2001) . The goal of this study was to provide further empirical support for the use of target rotations as a method for deriving a comparison model. Specifically, we conducted Monte Carlo analyses exploring: a) the use of the Schmid-Leiman (Schmid & Leiman, 1957) orthogonalization to specify a viable initial target matrix, and b) the recovery of true bifactor pattern matrices using target rotations as implemented in MPLUS (Asparouhov & Muthén, 2008) . Results suggest that to the degree that item response data conform to independent cluster structure, target rotations can be used productively to establish a plausible comparison model.