Processes | Pattern Discovery | Multidimensional Scaling

Multidimensional Scaling
The Multidimensional Scaling (MDS) process estimates the coordinates of a set of objects in a space of specified dimensionality that come from data measuring the distances between pairs of objects. The input data is usually a distance matrix, which can be created by the Distance Matrix and Clustering process. A 2D or 3D Scatterplot is generated based on the estimated coordinates.
MDS can be used as a data exploration tool to identify grouping patterns in the data.
For a more detailed description of MDS, refer to the SAS/STAT reference manual on PROC MDS.
What do I need?
One Input Data Set is required to run the Multidimensional Scaling process. This data set should be a square matrix. The adsl_diit_dmt.sas7bdat data set (from the included Nicardipine data) contains a square matrix.
The adsl_diit_dmt.sas7bdat data set was generated as previously described (see Distance Matrix and Clustering) from the adsl_diit.sas7bdat data set included with JMP Clinical.
For detailed information about the files and data sets used or created by JMP Life Sciences software, see Files and Data Sets.
Output/Results
The output generated by this process is summarized in a Tabbed report. Refer to the Multidimensional Scaling output documentation for detailed descriptions and guides to interpreting your results.