To Be or Not to Be Associated: Power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies

To Be or Not to Be Associated: Power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies

A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide st...

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Bibliographic Details
Main Authors: Elise eVaumourin, Gwenaël eVourc’h, Sandra eTelfer, Xavier eLambin, Diaeldin Ahmed Salih, Ulrike eSeitzer, Serge eMorand, Nathalie eCharbonnel, Muriel eVayssier-Taussat, Patrick eGasqui
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-05-01
Series:Frontiers in Cellular and Infection Microbiology
Subjects:
screening
modeling
interactions
network model
associations
GLM approach
Online Access:http://journal.frontiersin.org/Journal/10.3389/fcimb.2014.00062/full

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