User Guide

407
Distances
Distances Di
ssimilarity Measures
Figure 25-2
Distances Dissimilarity Measures dialog box
From the Measure group, select the alternative that corresponds to your type of data
(interval, count, or binary); then, from the drop-down list, select one of the measures
that corresponds to that type of data. Available measures, by data type, are:
 Interval data. Euclidean distance, squared Euclidean distance, Chebychev, block,
Minkowski, or customized.
 Count data. Chi-square measure or phi-square measure.
 Binary data. Euclidean distance, squared Euclidean distance, size difference,
pattern difference, variance, shape, or Lance and Williams. (Enter values for
Present and Absent to specify which two values are meaningful; Distances will
ignore all other values.)
The Transform Values group allows you to standardize data values for either cases or
variables before computing proximities. These transformations are not applicable to
binary data. Available standardization methods are z scores, range –1 to 1, range 0 to
1, maximum magnitude of 1, mean of 1, or standard deviation of 1.
The Transform Measures group allows you to transform the values generated by
the distance measure. They are applied after the distance measure has been computed.
Available options are absolute values, change sign, and rescale to 0–1 range.