Meta-analysis of prevalence


Autoria(s): Barendregt, Jan J.; Doi, Suhail A.; Lee, Yong Yi; Norman, Rosana E.; Vos, Theo
Data(s)

2013

Resumo

Meta-analysis is a method to obtain a weighted average of results from various studies. In addition to pooling effect sizes, meta-analysis can also be used to estimate disease frequencies, such as incidence and prevalence. In this article we present methods for the meta-analysis of prevalence. We discuss the logit and double arcsine transformations to stabilise the variance. We note the special situation of multiple category prevalence, and propose solutions to the problems that arise. We describe the implementation of these methods in the MetaXL software, and present a simulation study and the example of multiple sclerosis from the Global Burden of Disease 2010 project. We conclude that the double arcsine transformation is preferred over the logit, and that the MetaXL implementation of multiple category prevalence is an improvement in the methodology of the meta-analysis of prevalence.

Identificador

http://eprints.qut.edu.au/79814/

Publicador

BMJ Publishing Group

Relação

DOI:10.1136/jech-2013-203104

Barendregt, Jan J., Doi, Suhail A., Lee, Yong Yi, Norman, Rosana E., & Vos, Theo (2013) Meta-analysis of prevalence. Journal of Epidemiology and Community Health, 67(11), pp. 974-978.

Direitos

Copyright 2013 The Authors license to BMJ Publishing Group

Fonte

Faculty of Health; Institute of Health and Biomedical Innovation; School of Public Health & Social Work

Palavras-Chave #110000 MEDICAL AND HEALTH SCIENCES #111700 PUBLIC HEALTH AND HEALTH SERVICES #111706 Epidemiology #anzsrc Australian and New Zealand Standard Research Class #disease incidence #disease prevalence #estimation method #meta-analysis #methodology #software #article #binomial distribution #computer simulation #human #meta analysis #meta analysis (topic) #multiple sclerosis #prevalence #severity of illness index #statistical model #statistics #Humans #Logistic Models #Meta-Analysis as Topic #Models #Statistical
Tipo

Journal Article