Vaumourin, EliseVourc'h, GwenaelTelfer, SandraLambin, XavierSalih, DiaeldinSeitzer, UlrikeMorand, SergeCharbonnel, NathalieVayssier-Taussat, MurielGasqui, Patrick2015-01-272015-01-272014-05-15Vaumourin, E, Vourc'h, G, Telfer, S, Lambin, X, Salih, D, Seitzer, U, Morand, S, Charbonnel, N, Vayssier-Taussat, M & Gasqui, P 2014, 'To be or not to be associated : power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies', Frontiers in cellular and infection microbiology, vol. 4, 62. https://doi.org/10.3389/fcimb.2014.000622235-2988ORCID: /0000-0003-4643-2653/work/95222447ORCID: /0000-0002-9596-0711/work/166225448http://hdl.handle.net/2164/4206Acknowledgments We are grateful to the « Tiques et Maladies à Tiques » working group of the « Réseau Ecologie des Interactions Durables » for discussion and support. This modeling work was supported by the Animal Health department of National Institute of Agronomic Research (http://www.inra.fr), Auvergne region (http://www.auvergnesciences.com), the Metaprogramme MEM (projet Patho-ID) of INRA and the EU grant FP7-261504 EDENext. It is cataloged by the EDENext Steering Committee as EDENext208 (http://www.edenext.eu). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. The field vole fieldwork was supported by funding from the Natural Environment Research Council (grant GR3/13051) and the Wellcome Trust (grants 075202/Z/04/Z and 070675/Z/03/Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.111568360engassociationsinteractionsmodelingparasite communityscreeningGLM approachnetwork modelchi-square testcomponent community structurecentral equatoria stateLake District Regionmolecular-detectionSouthern SudanNorthern SpainnetworksBabesiapopulationTheileriaQR MicrobiologyQRJournal article10.3389/fcimb.2014.000624