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Form Similarity Matrix

Select menu: Data | Form Similarity Matrix

This dialog forms a similarity matrix from a set of variates. The similarity coefficient that is calculated allows variables to be qualitative, quantitative or dichotomous, or mixtures of these types; values of some of the variables may be missing for some samples. The values of a similarity coefficient vary between zero and unity: two samples have a similarity of unity only when both have identical values for all variables; a value of zero occurs when the values for the two samples differ maximally for all variables.

  1. After you have imported your data, from the menu select 
    Data | Form Similarity Matrix.

Available data

This lists data structures appropriate to the current input field. The contents will change as you move from one field to the next. You can double-click a name to copy it to the current input field or type it in.

Data values

This specifies the variates and the type of each variate. The similarity type of a variate determines how differences in variate values for each unit contribute to the overall similarity between units. Variates can be added to this list by double-clicking on a variate name within the Available data list. You can transfer multiple selections from Available data by holding the Ctrl key on your keyboard while selecting items, then click to move them all across in one action.

When a variate name is transferred from the Available data list the type for the variate is set using the measure within the Default type of test list. The type for a variate can be changed within the Data values list by double-clicking on the variate in this list and selecting a new similarity measure from the resulting dialog.

Similarity Measures

Jaccard is appropriate for dichotomous variables, simple matching for qualitative variables and the other settings give different ways for handling quantitative variables. The form of contribution to the similarity is as follows:

Type Contribution Weight
Jaccard if xi = xj = 1, then 1 1
  if xi = xj = 0, then 0 0
  if xi /= xj, then 0 1
Simple matching if xi = xj, then 1 1
  if xi /= xj, then 0 1
Dice if xi = xj = 1, then 1 1
  if xi = xj = 0, then 0 0
  if xi /= xj, then 0 0.5
Sneath and Sokal if xi = xj, then 1 1
  if xi /= xj, then 0 0.5
Russell and Rao if xi = xj, then 1 1
  if xi = 0 or xj = 0, then 0 1
Antidice if xi = xj = 1, then 1 1
  if xi = xj = 0, then 0 0
  if xi /= xj, then 0 2
Rogers and Tanimoto if xi = xj, then 1 1
  if xi /= xj, then 0 2
Cityblock 1 – |xi – xj| / range 1
Manhattan synonymous with cityblock  
Ecological 1 – |xi – xj| / range 1
  unless xi = xj = 0 0
Euclidean 1 – {(xi – xj) / range}2 1
Pythagorean synonymous with Euclidean  
Divergence 1 – {(xi – xj) / (xi + xj)}2 1
Canberra 1 – |xi – xj| / (|xi| + |xj|) 1/p
Bray and Curtis 1 – |xi – xj| xi + xj
Soergel 1 – |xi – xj| max(xi, xj)

The measure of similarity is formed by multiplying each contribution by the corresponding weight, summing all these values, and then dividing by the sum of the weights.

Default type of test

This specifies the default similarity used when items are added to the Data values list. For example, when you double-click on a variate name within the Available data list to transfer it to the Data values list.

Name of new matrix

Specifies the name of the identifier of a symmetric matrix to save the similarity matrix.

Unit labels

Lets you specify a text or variate which is to be used to label the rows of the similarity matrix.


Specifies which items of output are to be displayed in the Output window.

Similarity matrix A symmetric matrix of similarities .

Action Icons

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.

See also

  • FSIMILARITY directive for forming similarity matrices in command mode.
Updated on April 25, 2019

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