This paper deals with a framework of model order reduction for high-order parametric, linear systems. A set of low-order nonparametric systems with different reduced orders is computed for sample points. Then, two approaches are presented applying pseudoinverses for the introduction of generalized coordinates. Finally, a reduced system for a new parameter value is obtained by interpolating differently sized system matrices. The paper extends current methods to the general case where the local systems have different reduced orders.