1. K-Means Cluster Analysis of Rehabilitation Service Users in the Home Health Care System of Ontario: Examining the Heterogeneity of a Complex Geriatric Population  
Joshua J. Armstrong, MSc, Mu Zhu, PhD, John P. Hirdes, PhD, Paul Stolee, PhD 
Archives of Physical Medicine and Rehabilitation 
Volume 93, Issue 12, Pages (December 2012)
DOI: /j.apmr
Copyright © 2012 American Congress of Rehabilitation Medicine Terms and Conditions

2. Fig 1
Cluster proportions for dichotomous variables used in K-means cluster analysis. The variables are ordered by between-cluster variations (from high to low variation). Abbreviation: COPD, chronic obstructive pulmonary disease.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2012 American Congress of Rehabilitation Medicine Terms and Conditions

3. Fig 2
The colors in this heat map represent quantiles. Black boxes indicate the cluster is on the low end of the distribution for the particular variable. White boxes indicate that the cluster is on the high end of the distribution for the particular variable. Clusters are ordered in similarity to each other. Variables are ordered in similarity to each other, in terms of their distribution over the 7 clusters. Abbreviation: COPD, chronic obstructive pulmonary disease.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2012 American Congress of Rehabilitation Medicine Terms and Conditions