查看文章

The purpose of this study is to develop a statistical model to predict the risk for developing disease. In order to enrich our general understanding of schizophrenia disorder, several clustering techniques are used as a preliminary study. Schizophrenia is a heterogeneous decease with great variability in symptoms, cognition, biology and course of illness. Some of this variability may be explained by latent subgroups that differ in etiology and key features. Individuals with paternal age related schizophrenia (PARS) may represent such a subgroup as evidence suggests a distinct symptom profile. Using K-means and hierarchical clustering on a large sample of schizophrenia patients, this study examines demographic, clinical and the distinctiveness of latent PARS subgroups.