Homogeneity Analysis (HOMALS) is a statistical visualization technique for picturing the associations between the levels of a set of categorical variables, and the similarities between the objects which these categories are applied too. The goal is to have a global view of the data that is useful for exploratory proposes. Only the categorical variables are included in the analysis.

Homogeneity Analysis assigns scores to the objects and it quantifies categories (optimal scaling). These scores and quantifications allow to construct a representation of the data estructure in a low dimensional space (data reduction).

Categories and objects are represented as points in a joint space. The positions of the object points are related with their similarities. Objects with similar profile are located closely in the space. A category point is the centroid of the objects that belong to this category.

Homogeneity Analysis visualization displays the graphs for the category quantification and the objects scores, and let you interactively modify the dimensions of the HOMALS solution. Also, a plot for evaluating the fit of the solution and the discrimination measures of the variables is included.

