While the study of macroparasites usually uses quantitative data (i.e., parasite load per individual host), the study of microparasites on the field is most of the time limited to presence-absence data (i.e., serology), making the detection of associations between parasites more complicated from a methodological point of view. The corrected chi-square proposed in this study is, with the logistic regression approach, currently one of the rare ways to search for interaction between parasites from presence-absence data. This work provides evidence of the efficiency of such methods to reduce the bias introduced by common risk factors and encourages their use. However it also points out the low robustness of the likelihood ratio test for certain data characteristics. The corrected chi-square test must indeed be preferred for small sample size.