mixdata

<p>Simulated dataset with quantitative, ordinal and categorical variables. Some variables are correlated and some are associated to sample groups.</p>

datasets

Provides utilities for clustering subjects and variables of mixed data types (Hummel, Edelmann, Kopp-Schneider (2017) <doi: 10.1371/journal.pone.0188274>). Similarities between subjects are measured by Gower's general similarity coefficient with an extension of Podani for ordinal variables. Similarities between variables can be assessed i) by combination of appropriate measures of association for different pairs of data types or ii) based on distance correlation. Alternatively, variables can also be clustered by the 'ClustOfVar' approach. The main feature of the package is the generation of a mixed-data heatmap. For visualizing similarities between either subjects or variables, a heatmap of the corresponding distance matrix can be drawn. Associations between variables can be explored by a 'confounder plot', which allows visual detection of possible confounding, collinear, or surrogate factors for some variables of primary interest. Distance matrices and dendrograms for subjects and variables can be derived and used for further visualizations and applications. This work was supported by BMBF grant 01ZX1609B, Germany.

Manuela Hummel

CluMix

Clustering and Visualization of Mixed-Type Data

mixdata function

<p><code>mixdata</code> is a data frame with 40 samples (rows) and 10 variables (columns). The variable names indicate their type, i.e. '.quant' (quantitative), '.ord' (ordinal), '.cat' (categorical).</p>

mixdata: Small example dataset with variables of different types

Description

Usage

Arguments

Format

Examples