The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary
AuthorPorgo, T; Norris, SL; Salanti, G; Johnson, LF; Simpsons, JA; Low, N; Egger, M; Althaus, CL
Source TitleResearch Synthesis Methods
University of Melbourne Author/sSimpson, Julie
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsPorgo, T., Norris, S. L., Salanti, G., Johnson, L. F., Simpsons, J. A., Low, N., Egger, M. & Althaus, C. L. (2019). The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary. RESEARCH SYNTHESIS METHODS, 10 (1), pp.125-133. https://doi.org/10.1002/jrsm.1333.
Access StatusOpen Access
Mathematical modeling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision-making, particularly when data from systematic reviews of primary studies do not adequately answer a research question. However, systematic reviewers and guideline developers may struggle with using the results of modeling studies, because, at least in part, of the lack of a common understanding of concepts and terminology between evidence synthesis experts and mathematical modellers. The use of a common terminology for modeling studies across different clinical and epidemiological research fields that span infectious and non-communicable diseases will help systematic reviewers and guideline developers with the understanding, characterisation, comparison, and use of mathematical modeling studies. This glossary explains key terms used in mathematical modeling studies that are particularly salient to evidence synthesis and knowledge translation in clinical medicine and public health.
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