This work aims to evaluate the use of parametric models instead of a nonparametric procedure to adjust survival curves related to different treatments, and to verify the equivalence among treatments by the multivariate method of cluster analysis. The dataset used to validate the method was obtained from a laboratory experiment with cutting ants. Eight colonies of cutting ants were used, each one receiving different treatments. The exponential, Weibull, log-normal, and logistic models were adjusted for each treatment, along with the usual Kaplan-Meier adjustment. The logistic model used was the best option for evaluating the survival of the ants. Therefore, this model was adjusted for each treatment. The estimates of the parameters of each adjusted model were clustered using Ward's method of multivariate technique of cluster analysis. Finally, heuristic techniques for choosing the number of clusters were applied in order to define the sets of equivalent treatments. For the dataset used, the proposed method was less laborious and as efficient as the logrank for the comparison of many survival curves.
logrank test; cluster analysis; curves comparison
