| Literature DB >> 24905478 |
Fanny Feuillet1, Lise Bellanger, Jean-Benoit Hardouin, Caroline Victorri-Vigneau, Véronique Sébille.
Abstract
The high consumption of psychotropic drugs is a public health problem. Rigorous statistical methods are needed to identify consumption characteristics in post-marketing phase. Agglomerative hierarchical clustering (AHC) and latent class analysis (LCA) can both provide clusters of subjects with similar characteristics. The objective of this study was to compare these two methods in pharmacoepidemiology, on several criteria: number of clusters, concordance, interpretation, and stability over time. From a dataset on bromazepam consumption, the two methods present a good concordance. AHC is a very stable method and it provides homogeneous classes. LCA is an inferential approach and seems to allow identifying more accurately extreme deviant behavior.Entities:
Keywords: Agglomerative hierarchical clustering; Clusters comparison; Clusters stability; Drug dependence; Latent class analysis; Multiple correspondence analysis
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Year: 2015 PMID: 24905478 DOI: 10.1080/10543406.2014.920855
Source DB: PubMed Journal: J Biopharm Stat ISSN: 1054-3406 Impact factor: 1.051