Work

A Bayesian multivariate meta‐analysis of prevalence data

Year: 2020

Type: review

Study design: Systematic Review

Abstract: When conducting a meta-analysis involving prevalence data for an outcome with several subtypes, each of them is typically analyzed separately using a univariate meta-analysis model. Recently, multivariate meta-analysis models have been shown to correspond to a decrease in bias and variance for multiple correlated outcomes compared with univariate meta-analysis, when some studies only report a subset of the outcomes. In this article, we propose a novel Bayesian multivariate random effects model to account for the natural constraint that the prevalence of any given subtype cannot be larger than that of the overall prevalence. Extensive simulation studies show that this new model can reduce bias and variance when estimating subtype prevalences in the presence of missing data, compared with standard univariate and multivariate random effects models. The data from a rapid review on occupation and lower urinary tract symptoms by the Prevention of Lower Urinary Tract Symptoms Research Consortium are analyzed as a case study to estimate the prevalence of urinary incontinence and several incontinence subtypes among women in suspected high risk work environments.

Source: Statistics in Medicine

DOI: 10.1002/sim.8593

Authors: Lianne Siegel, Kyle Rudser, Siobhan Sutcliffe, Alayne Markland, Linda Brubaker, Sheila Gahagan, Ann E. Stapleton, Haitao Chu

Institutions: University of Minnesota, Washington University in St. Louis, University of Alabama at Birmingham, Birmingham VA Medical Center, UAB Medicine, University of California San Diego, University of Washington

Language: English

Topic: Meta-analysis and systematic reviews

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, U.S. National Library of Medicine

Awards: The Truly Healthy Bladder 2: Understanding Normal As A Pathway To Prevention Of Lower Urinary Tract Symptoms In Women, Penn+Plus Clinical Research Center, Training in Biostatistics for Heart, Lung and Blood Disease Research, Pathways to Lower Urinary Tract Symptoms Prevention in Adolescent and Adult Women., Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium Yale Clinical Research Center, Joint Meta-Regression Methods Accounting for Postrandomization Variables, Statistical Methods and Software for Multivariate Meta-analysis, Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium Scientific and Data Coordinating Center, Prevention of LUTS: Bladder Health Clinical Center, UC San Diego Site, Bladder health promotion and LUTS prevention inadolescent and adult women across the life course, PLUS Loyola Clinical Center, G7558943547, Prevention of Lower Urinary Tract Symptoms in Women: Bladder Health Scientific and Data Coordinating Center (PLUS-SDCC) (U01)

OpenAlex ID: W3033344178

FWCI: 0.259

Cites: 44

Cited by: 8

Related to: 10