Create Measure from Data
Multidimensional scaling uses dissimilarity data to create a scaling solution. If your data are multivariate data (values of measured variables), you must create dissimilarity data in order to compute a multidimensional scaling solution. You can specify the details of creating dissimilarity measures from your data.
Measure. Allows you to specify the dissimilarity measure for your analysis. Select one alternative from the Measure group corresponding to your type of data, and then select one of the measures from the drop-down list corresponding to that type of measure. Available alternatives are:
- Interval. Euclidean distance, Squared Euclidean distance, Chebychev, Block, Minkowski, or Customized.
- Counts. Chi-square measure or Phi-square measure.
- Binary. Euclidean distance, Squared Euclidean distance, Size difference, Pattern difference, Variance, or Lance and Williams.
Create Distance Matrix. Allows you to choose the unit of analysis. Alternatives are Between variables or Between cases.
Transform Values. In certain cases, such as when variables are measured on very different scales, you want to standardize values before computing proximities (not applicable to binary data). Select a standardization method from the Standardize drop-down list (if no standardization is required, select None).
Selecting a Measure
This feature requires the Categories option.
- From the
menus choose:
- Choose to create proximities from the data in the Data Format dialog box and click Define.
- In the Create Proximities from Data dialog box, click Measure.
- Select a data type (Interval, Counts, or Binary).
- Select a dissimilarity measure from the appropriate drop-down list.