USING LATENT CLASS ANALYSIS TO MODEL PREFERENCE HETEROGENEITY IN HEALTH- A SYSTEMATIC REVIEW

Author(s)

Zhou M, Thayer WM, Bridges JF
Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

OBJECTIVES: We sought to document the applications of LCA in the stated-preference literature focusing on health and to inform future studies by identifying current norms in published applications. METHODS: We conducted a systematic review of the MEDLINE, Embase, EconLit, Web of Science, and PsycINFO databases. We included English-language stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two reviewers independently reviewed titles, abstracts, and texts. Key outcomes extracted included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality was assessed using the PREFS quality checklist. RESULTS:

Conference/Value in Health Info

2017-05, ISPOR 2017, Boston, MA, USA

Value in Health, Vol. 20, No. 5 (May 2017)

Code

PRM154

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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