Because conducting experimental coinfections is intractable in most parasite systems, inferences about the presence and strength of interspecific interactions in parasite communities are often made from analyses of field data. It is unclear whether methods used to test for competition are able to detect competition in field-collected datasets. Data from a study of the intestinal helminth communities of creek chub (Semotilus atromaculatus) were used to explore the potential of commonly available methods to detect negative interactions among parasite species in species-poor, low-intensity communities. Model communities were built in the absence of competition and then modified by four modes of competition. Both parametric and null model approaches were utilized to analyze modelled parasite communities to determine the conditions under which competitive interactions were discerned. Correlations had low Type I error rates but did not reliably detect competition, when present, at a statistically significant level. Results from logistical regressions were similar but showed improved statistical power. Results from null model approaches varied. Envelope analyses had near ideal properties when parasite prevalence was high but had high Type I error rates in low prevalence communities. Co-occurrence analyses demonstrated promising results with certain co-occurrence metrics and randomization algorithms, but also had many more cases of failure to detect competition when present and/or reject competition when it was absent. No analytical approach was clearly superior, and the variability observed in the present investigation mirrors similar efforts, suggesting that clear guidelines for detecting competition in parasite communities with observational data will be elusive.