To be or not to be associated : power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies
Citation
Vaumourin , 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.2014.00062