title: On Comparison of Clustering Methods for Pharmacoepidemiological Data.
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.
authors.affiliation: a EA 4275 SPHERE Biostatistics, Pharmacoepidemiology and Human Sciences Research , University of Nantes , Nantes , France.
authors.forename: Fanny
authors.initials: F
authors.lastname: Feuillet
authors.forename: Lise
authors.initials: L
authors.lastname: Bellanger
authors.forename: Jean-Benoit
authors.initials: JB
authors.lastname: Hardouin
authors.forename: Caroline
authors.initials: C
authors.lastname: Victorri-Vigneau
authors.forename: Véronique
authors.initials: V
authors.lastname: Sébille
mesh_terms: D000465:Algorithms; D014151:Anti-Anxiety Agents / Q000494:pharmacology*; D001960:Bromazepam / Q000494:pharmacology; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D006801:Humans; D017891:Pharmacoepidemiology / Q000379:methods / Q000706:statistics & numerical data*
chemical_list: D014151:Anti-Anxiety Agents; D001960:Bromazepam
keywords: Agglomerative hierarchical clustering; Clusters comparison; Clusters stability; Drug dependence; Latent class analysis; Multiple correspondence analysis