This work discusses and demonstrates the novel use of multivariate analysis and data dimensionality reduction techniques to handle the variety and complexity of data generated in efficacy trials for the development of a prototype vaccine to protect sheep against the Teladorsagia circumcincta nematode. A curated collection of data dimension reduction and visualisation techniques, in conjunction with sensible statistical modelling and testing which explicitly model key features of the data, offers a synthetic view of the relationships between the multiple biological parameters measured. New biological insight is gained into the patterns and associations involving antigen-specific antibody levels, antibody avidity and parasitological parameters of efficacy that is not achievable by standard statistical practice in the field. This approach can therefore be used to guide vaccine refinement and simplification through identifying the most immunologically relevant antigens, and it can be analogously implemented for similar studies in other areas. To facilitate this, the associated data and computer codes written for the R open system for statistical computing are made freely available.