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eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

When are summary ROC curves appropriate for diagnostic meta-analyses?

Author(s): F. M. Chappell, G. M. Raab, J. M. Wardlaw

Abstract:
Diagnostic tests are increasingly evaluated with systematic reviews and this has lead to the recent developments of statistical methods to analyse such data. The most commonly used method is the summary receiver operating characteristic (SROC) Curve, which can be fitted with a non-linear bivariate random-effects model. This paper focuses on the practical problems of interpreting and presenting data from such analyses. First, many meta-analyses may be underpowered to obtain reliable estimates of the SROC parameters. Second, the SROC model may be inappropriate. In these situations, a summary with two univariate meta-analyses of the true and false positive rates (TPRs and FPRS) may be more appropriate. We characterize the type of problems that can occur in fitting these models and present an algorithm to guide the analyst of such studies, with illustrations from analyses of published data. A set of R functions, freely available to perform these analyses, can be downloaded from (www.diagmeta.info). Copyright (C) 2009 John Wiley & Sons, Ltd.

Full version: Available here

Click the link to go to an external website with the full version of the paper


ISBN: 0277-6715
Publication Year: 2009
Periodical: Statistics in Medicine
Periodical Number: 21
Volume: 28
Pages: 2653-2668
Author Address: