Latent class analysis identification of syndromes in alzheimer's disease: a bayesian approach

Walsh, Cathal D. (avtor)

Latent variable models have been used extensively in the social sciences. In this work a latent class analysis is used to identify syndromes within Alzheimer's disease. The fitting of the model is done in a Bayesian framework,and this is examined in detail here. In particular, the label switching problem is identified, and solutions presented. Graphical summaries of the posterior distribution are included.

• Jezik: Angleški jezik
• Vrsta gradiva: Delo ni kategorizirano
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FDV - Fakulteta za družbene vede
• Leto izida: 2006
• Št. strani: Str. 147-162
• Številčenje: Vol. 3, no. 1
• PID: 20.500.12556/RUL-8446
• UDK: 303
• ISSN pri članku: 1854-0023
• COBISS.SI-ID: 25331805
• Datum objave v RUL: 11.07.2014

WALSH, Cathal D., 2006, Latent class analysis identification of syndromes in alzheimer’s disease: a bayesian approach. Advances in methodology and statistics [na spletu]. 2006. Vol. 3, no. 1, p. 147–162. [Dostopano 1 maj 2025]. Pridobljeno s: http://mrvar.fdv.uni-lj.si/pub/mz/mz3.1/walsh.pdf

Gradivo je del revije

• Naslov: Advances in methodology and statistics
• Skrajšan naslov: Metodol. zv.
• Založnik: Fakulteta za družbene vede
• ISSN: 1854-0023
• COBISS.SI-ID: 215795712