A comparison of confidence interval methods for habitat use-availability studies

Wildlife managers routinely compute sets of simultaneous confidence intervals to estimate the actual proportion of use of a set of k habitat types. Confidence intervals are determined by assuming that the counts of observed use are from k binomial populations. A set of k intervals is constructed from a large sample approximation for a confidence interval for a single binomial proportion. The simultaneous confidence level is controlled by use of the Bonferroni inequality. The coverage probability of these intervals can be less than the nominal (1 - alpha) 100% level. This paper presents results of a simulation study comparing the performance of these intervals with 3 alternatives; the usual method with a continuity correction factor, and 2 methods of computing confidence intervals for multinomial proportions. The 2 latter methods are superior and should be used in place of the binomial intervals.