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Abstract
In this study we aim at developing an adequate representation of grid data gathered with Hermans' Self-Confrontation Method (SCM). For a large sample of grids (N = 127), a Principal Component Algorithm (KUNGRID) and a Multidimensional Scaling Algorithm (ALSCAL) are both applied in order to assess the quality of the geometrical representations of valuations in affect space. The results show that both techniques yield comparable high quality depictions in a two-dimensional plane. Either of them can be used as a tool in facilitating the interpretation of idiographic grids in both research and clinical practice with the Self-Confrontation Method. An SPSS® control file for use with ALSCAL is included in the Appendix. The program KUNGRID can be obtained at the Computer Services Group1 of the University of Nijmegen.