Making reliable decisions in the study of wildlife diseases: using hypothesis tests, statistical power, and observed effects.

The increasing importance of wildlife diseases in conservation efforts places an additional importance on research study design, data analysis, and interpretation. In this paper, we explore the design and analysis of wildlife disease data with regard to hypothesis testing, statistical power, sample sizes, the relative costs of type I versus type II errors, and effect size. To illustrate these ideas, we conducted a literature review of the Journal of Wildlife Diseases (JWD), ran computer simulations that estimate type II error rates for statistical techniques commonly used in JWD, and reanalyzed previously published data on disease prevalence.