Abstract
Abstract In epidemiology, when antibiotic efficacy is compared between two treatment groups, treating fish survival time as a continuous rather than as a discrete variable is more sensitive and appropriate for detecting group differences when the data contain censored observations. By using nonparametric methods for analysis of survival or failure time, we evaluated distributional rather than proportional differences between treatment groups, and treatment efcacies were determined by comparing probabilities of survival longer than a specified time. To illustrate the utility of survival analysis (i.e., analysis of survival times), a nonstandard, “messy” data set containing censored observations was examined for treatment effects. Survival analysis and standard statistical methods were used to analyze the same data set. With survival analysis, there was a significant difference (P < 0.05) between treatments when distributions of survival times were compared. However, standard statistical methods failed to s...
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