A probabilistic approach to the statistical analysis of experiments on helminth parasites

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Abstract
A probabilistic method, based on a Bayesian approach, is proposed for the evaluation of results obtained in experimental infections induced by microscopic eggs (or larvae) whose exact number is not directly known. The statistical analysis leads to the evaluation of the probability that the eggs (or larvae) develop “normally”; the results are represented by normalized likelihood functions (NLF) or, more generally, through final probability distributions. Any difference in the various experiments that possibly emerged may be judged on the NLF graphs. Some real and fictional cases are discussed as examples. In particular, the unreliability of the usual method that considers only the number of recovered parasites but not the number of eggs used may be easily verified.

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