A Bayesian multivariate approach to estimating the prevalence of a superordinate category of disorders. Issue 4 (14th September 2018)

• Record Type: Journal Article
• Authors: Fawcett, Jonathan M.; Fairbrother, Nichole; Fawcett, Emily J.; White, Ian R.
• Is Part Of: International journal of methods in psychiatric research. Volume 27:Issue 4(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-09-14
• Subjects: Bayesian modelling -- epidemiology -- methods -- multivariate model -- meta‐analysis; Psychiatry -- Research -- Methodology -- Periodicals; Psychiatry -- Periodicals; 616.890072
• DOI: 10.1002/mpr.1742
• Languages: English
• ISSNs: 1049-8931

Abstract

Abstract: Objective: Epidemiological research plays an important role in public health, facilitated by the meta‐analytic aggregation of epidemiological trials into a single, more powerful estimate. This form of aggregation is complicated when estimating the prevalence of a superordinate category of disorders (e.g., "any anxiety disorder, " "any cardiac disorder") because epidemiological studies rarely include all of the disorders selected to define the superordinate category. In this paper, we suggest that estimating the prevalence of a superordinate category based on studies with differing operationalization of that category (in the form of different disorders measured) is both common and ill‐advised. Our objective is to provide a better approach. Methods: We propose a multivariate method using individual disorder prevalences to produce a fully Bayesian estimate of the probability of having one or more of those disorders. We validate this approach using a recent case study and parameter recovery simulations. Results: Our approach produced less biased and more reliable estimates than other common approaches, which were at times highly biased. Conclusion: Although our approach entails additional effort (e.g., contacting authors for individual participant data), the improved accuracy of the prevalence estimates obtained is significant and therefore recommended.