05-03-2012 06:58 PM
Hi everyone, I have read this interesting paragraph about cluster analysis, nut I would like to understand (bold face) it better,
with an specific example.
Clustering systems assign objects into groups (or called clusters) so that objects from the same cluster are
more similar to each other than objects from different clusters. Cluster analysis contains many diverse
methodologies for exploring structure within complex data contents, which is a technique for classifying data
cases into distinct groups on the basis of similarity across variables. Usually, in biomedicine, this means that
we are interested in clustering groups of patients or genes. So, in a sense it’s the opposite of factor analysis:
instead of forming groups of variables based on a number of patients’ responses to those variables, we
instead group patients based on their responses to several variables.
Several variables....can anyone write down some specific example in a clinical trial, what variables are involved:
Thanks in advance,
05-04-2012 08:30 AM
Variables could include standard demographics like age, gender, disease history, or medication status. What strikes me as an interesting addition to these are genomic variables--presence or absence of any number of genes in the individual. All of this could be fed into a clustering algorithm.