Computes a distance matrix comparing variables or cases.
Technical details
Description
If a case contains missing values, it is omitted from the analysis. Weights are not applicable when comparing cases. See What is a Distance Matrix? for more information about distance matrices.
Inputs

Compare Whether variables or cases are to be compared. You can only compare 100 cases or fewer.
 Case labels If cases are compared, these are the labels to use to refer to each case. Otherwise, the case index is used.

Variables The variables that will be included in this analysis.
 Variable names Whether to display Variable Names in the output instead of Variable Labels.
 Categorical as binary Represents unordered categorical variables as binary variables. Otherwise, they are represented as sequential integers (i.e., 1 for the first category, 2 for the second, etc.). Numeric  Multi variables are treated according to their numeric values and not converted to binary.
 Measure Whether to measure similarities or dissimilarities.

Similarity measure The type of similarity measure to use:
 Correlation Pearson correlation.
 Cosine The cosine of the angle between a pair of vectors which represent a pair of variables or cases.

Distance measure The type of distance/dissimilarity measure to use. The options are (refer to dist for more information):
 Euclidean
 Squared Euclidean The square of the Euclidean distance
 Maximum
 Manhattan

Minkowski
 Minkowski power (p) The power parameter for the Minkowski distance measure.

Data standardization The standardization method. Choices include:
 None No standardization is performed.
 zscores Values are transformed to have mean zero and a standard deviation of one.
 Range [1,1] Values are divided by their range.
 Range [0,1] Values are subtracted by their minimum value and divided by their range.
 Mean of 1 Values are divided by their mean. If the mean is zero, the values will be unchanged.
 Standard deviation of 1 Values are divided by their standard deviation.
 For methods that require variation in the values (zscores, Range [1,1], Range [0,1] and Standard deviation of 1), if there is no variation in the values, they will be set to zero instead.
 Standardize by Whether to standardize by variables or cases.
 Measure transformation Transformation of the measures. Choices include None, Absolute values, Reverse sign and Range [0,1]. For Range [0,1], measures on the diagonal are ignored in the transformation.
 Show cell values Whether to display cell values, or if this should be determined based on an estimate of available space (Automatic).
 Show row labels Whether to display row labels.
 Show column labels Whether to display column labels.
Output
Acknowledgements
Uses the R package weights and the d3heatmap htmlwidget.
Method
 In Displayr: How to Create a Distance Matrix
 In Q: How to Create a Distance Matrix