Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated item parameters so that dimensions are aligned. Both the DDA and LRA methods are applied to real and simulated data, and it is demonstrated that both methods are broadly effective for achieving aligned scales. The routine use of scale alignment methods is recommended prior to comparing scores across dimensions.