Select menu: Stats | Multivariate Analysis | Multidimensional Scaling
Multidimensional scaling operates on a symmetric matrix whose values may be interpreted, in a general sense, as distances between a set of objects. The objective is to find a set of coordinates whose inter-point distances match, as closely as possible, those of the input data matrix. When plotted, the coordinates provide a display which can be interpreted in the same way as a map: for example, if points in the display are close together, their distance apart in the data matrix was small.
- After you have imported your data, from the menu select
Stats | Multivariate Analysis | Multidimensional Scaling.
- Fill in the fields as required then click Run.
This lists symmetric matrices that can be used to specify the distance data. Double-click a name to copy it to the current input field or type the name.
Specifies the symmetric matrix of inter-point distances.
Controls whether metric or non-metric scaling is given. The algorithm involves regression of the distances, calculated from the solution coordinates, against the distances in the data matrix. Non-metric scaling uses monotonic regression, whereas metric scaling uses linear regression through the origin.
Number of dimensions
Sets the number of dimensions required for the solution. Entering a list of numbers carries out a series of scaling operations, all based on the same matrix of dissimilarities, but with different numbers of dimensions.
You can control various aspects of the algorithm used for the analysis from the Options menu, and also select which results are to be printed.
|Pin||Controls whether to keep the dialog open when you click Run. When the pin is down the dialog will remain open, otherwise when the pin is up the dialog will close.|
|Restore||Restore names into edit fields and default settings.|
|Clear||Clear all fields and list boxes.|
|Help||Open the Help topic for this dialog.|